Triple
T349607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juno Beach |
E7412
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Mike and Nan sectors
Mike and Nan sectors were code names for specific landing areas on Juno Beach used by Allied forces during the D-Day invasion of Normandy in World War II.
|
E44325
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Mike and Nan sectors | Statement: [Juno Beach, alsoKnownAs, Mike and Nan sectors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike and Nan sectors Context triple: [Juno Beach, alsoKnownAs, Mike and Nan sectors]
-
A.
Onex
Onex is a suburban municipality in western Switzerland located just outside the city of Geneva.
-
B.
Sloan
Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
-
C.
Nourse
Nourse is a surname and variant spelling of "Nurse," historically associated with English-speaking families and occasionally used as a place or business name.
-
D.
Meraki
Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
-
E.
The Hub
The Hub is a well-known nickname for Boston, Massachusetts, reflecting its historical role as a central cultural, intellectual, and political center in the United States.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mike and Nan sectors Triple: [Juno Beach, alsoKnownAs, Mike and Nan sectors]
Generated description
Mike and Nan sectors were code names for specific landing areas on Juno Beach used by Allied forces during the D-Day invasion of Normandy in World War II.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike and Nan sectors Target entity description: Mike and Nan sectors were code names for specific landing areas on Juno Beach used by Allied forces during the D-Day invasion of Normandy in World War II.
-
A.
Onex
Onex is a suburban municipality in western Switzerland located just outside the city of Geneva.
-
B.
Sloan
Sloan is a surname most notably associated with Alfred P. Sloan, the influential long-time president and chairman of General Motors.
-
C.
Nourse
Nourse is a surname and variant spelling of "Nurse," historically associated with English-speaking families and occasionally used as a place or business name.
-
D.
Meraki
Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
-
E.
The Hub
The Hub is a well-known nickname for Boston, Massachusetts, reflecting its historical role as a central cultural, intellectual, and political center in the United States.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb1dc5f88190b54d084c6def7fc5 |
completed | Feb. 28, 2026, 1:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3d7ee59bc819080c417f7bc4eba3c |
completed | March 1, 2026, 6:08 a.m. |
| NEDg | Description generation | batch_69a3d896730881909e931e289a0386b6 |
completed | March 1, 2026, 6:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3d9665610819084739d23f3a14816 |
completed | March 1, 2026, 6:15 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.