Triple
T14214605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karen Crowder |
E352314
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
U-North
U-North is a powerful fictional agrochemical corporation central to the legal and ethical conflict in the film "Michael Clayton."
|
E1086122
|
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: U-North | Statement: [Karen Crowder, employer, U-North]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: U-North Context triple: [Karen Crowder, employer, U-North]
-
A.
Nord 260
The Nord 260 was a French twin-turboprop regional airliner prototype that served as the basis for the later Aérospatiale N 262.
-
B.
UC-64 Norseman
The UC-64 Norseman is a rugged, single-engine Canadian bush plane widely used by Allied forces in World War II for transport and utility missions.
-
C.
Uspantek
Uspantek is a Mayan language spoken by the Uspanteko people in the highlands of Guatemala.
-
D.
UNOV
UNOV is one of the main United Nations headquarters, located in Vienna, Austria, hosting various UN offices and agencies focused on issues such as drugs and crime, outer space affairs, and industrial development.
-
E.
Nuska
Nuska is a Mesopotamian god of fire and light, often serving as a divine vizier and attendant to major deities in the Sumerian and Akkadian pantheons.
- 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: U-North Triple: [Karen Crowder, employer, U-North]
Generated description
U-North is a powerful fictional agrochemical corporation central to the legal and ethical conflict in the film "Michael Clayton."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: U-North Target entity description: U-North is a powerful fictional agrochemical corporation central to the legal and ethical conflict in the film "Michael Clayton."
-
A.
Nord 260
The Nord 260 was a French twin-turboprop regional airliner prototype that served as the basis for the later Aérospatiale N 262.
-
B.
UC-64 Norseman
The UC-64 Norseman is a rugged, single-engine Canadian bush plane widely used by Allied forces in World War II for transport and utility missions.
-
C.
Uspantek
Uspantek is a Mayan language spoken by the Uspanteko people in the highlands of Guatemala.
-
D.
UNOV
UNOV is one of the main United Nations headquarters, located in Vienna, Austria, hosting various UN offices and agencies focused on issues such as drugs and crime, outer space affairs, and industrial development.
-
E.
Nuska
Nuska is a Mesopotamian god of fire and light, often serving as a divine vizier and attendant to major deities in the Sumerian and Akkadian pantheons.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de620f07bc81909212dcd1c91b5f95 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd1959f3d481909c15730bbd6f4748 |
completed | May 7, 2026, 10:59 p.m. |
| NEDg | Description generation | batch_69fd1a88fd948190b5d78a4ca4acdb94 |
completed | May 7, 2026, 11:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd1b2ed7748190b3f787f1b64c8831 |
completed | May 7, 2026, 11:07 p.m. |
Created at: April 10, 2026, 1:06 a.m.