Triple
T8891271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crocker |
E211680
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Ian Crocker
Ian Crocker is an American former competitive swimmer and multiple Olympic gold medalist known for his world records in butterfly events.
|
E783592
|
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: Ian Crocker | Statement: [Crocker, hasNotableBearer, Ian Crocker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ian Crocker Context triple: [Crocker, hasNotableBearer, Ian Crocker]
-
A.
Lee Crocker
Lee Crocker is a software engineer and developer known for his contributions to early web technologies and open-source projects.
-
B.
Ian Crafford
Ian Crafford is a film editor best known for his work on the James Bond movie "Never Say Never Again."
-
C.
Eric Crozier
Eric Crozier was a British theatrical director, producer, and writer best known for his close collaboration with composer Benjamin Britten on several operas.
-
D.
Rob Couhig
Rob Couhig is an American businessman and lawyer known for owning and leading English football club Wycombe Wanderers.
-
E.
Martin Boddey
Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
- 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: Ian Crocker Triple: [Crocker, hasNotableBearer, Ian Crocker]
Generated description
Ian Crocker is an American former competitive swimmer and multiple Olympic gold medalist known for his world records in butterfly events.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ian Crocker Target entity description: Ian Crocker is an American former competitive swimmer and multiple Olympic gold medalist known for his world records in butterfly events.
-
A.
Lee Crocker
Lee Crocker is a software engineer and developer known for his contributions to early web technologies and open-source projects.
-
B.
Ian Crafford
Ian Crafford is a film editor best known for his work on the James Bond movie "Never Say Never Again."
-
C.
Eric Crozier
Eric Crozier was a British theatrical director, producer, and writer best known for his close collaboration with composer Benjamin Britten on several operas.
-
D.
Rob Couhig
Rob Couhig is an American businessman and lawyer known for owning and leading English football club Wycombe Wanderers.
-
E.
Martin Boddey
Martin Boddey was a British character actor known for his frequent supporting roles in mid-20th-century films and television, often portraying authority figures such as policemen and officials.
- 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_69ca83907954819096d52a245b635841 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61ba33c48190a657fc4147a326c0 |
completed | April 1, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05be377988190a59f0033322d627f |
completed | April 4, 2026, 12:31 a.m. |
| NEDg | Description generation | batch_69d05cb45280819096747ff8f7d5c2a0 |
completed | April 4, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d05d5d29f4819081c28b24cb2058b0 |
completed | April 4, 2026, 12:37 a.m. |
Created at: March 30, 2026, 6:54 p.m.