Triple
T16283329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Boston |
E395323
|
entity |
| Predicate | hullNumber |
P3152
|
FINISHED |
| Object |
C-1
C-1 is the hull classification symbol identifying USS Boston as the first protected cruiser in the United States Navy’s “C” cruiser series.
|
E1203390
|
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: C-1 | Statement: [USS Boston, hullNumber, C-1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: C-1 Context triple: [USS Boston, hullNumber, C-1]
-
A.
C-1
C-1 is a commuter rail line in the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
B.
C-2
C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
C.
C-3
C-3 is one of the main commuter rail lines in the Cercanías Madrid network, connecting central Madrid with several southern suburbs and surrounding municipalities.
-
D.
C-10
C-10 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
E.
C110
The C110 is a Honda Super Cub variant, a small, reliable, and fuel-efficient underbone motorcycle popular for everyday commuting.
- 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: C-1 Triple: [USS Boston, hullNumber, C-1]
Generated description
C-1 is the hull classification symbol identifying USS Boston as the first protected cruiser in the United States Navy’s “C” cruiser series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: C-1 Target entity description: C-1 is the hull classification symbol identifying USS Boston as the first protected cruiser in the United States Navy’s “C” cruiser series.
-
A.
C-1
C-1 is a commuter rail line in the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
B.
C-2
C-2 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
C.
C-3
C-3 is one of the main commuter rail lines in the Cercanías Madrid network, connecting central Madrid with several southern suburbs and surrounding municipalities.
-
D.
C-10
C-10 is a commuter rail line within the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
-
E.
C110
The C110 is a Honda Super Cub variant, a small, reliable, and fuel-efficient underbone motorcycle popular for everyday commuting.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24912c5808190a0d9c9f491315068 |
completed | April 17, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017c6b72081908a21e5099f463b62 |
completed | May 10, 2026, 5:29 a.m. |
| NEDg | Description generation | batch_6a001876efb081909c0940ebcf265f15 |
completed | May 10, 2026, 5:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0018f6de84819087b8e97b0400c77d |
completed | May 10, 2026, 5:34 a.m. |
Created at: April 10, 2026, 5:05 a.m.