Triple
T10983819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiram College |
E259574
|
entity |
| Predicate | hasPresident |
P112
|
FINISHED |
| Object |
David P. Haney
David P. Haney is an American academic administrator who has served as president of Hiram College in Ohio.
|
E1010298
|
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: David P. Haney | Statement: [Hiram College, hasPresident, David P. Haney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David P. Haney Context triple: [Hiram College, hasPresident, David P. Haney]
-
A.
Eric L. Haney
Eric L. Haney is a former U.S. Army Delta Force operator and author known for his memoir "Inside Delta Force," which inspired the television series "The Unit."
-
B.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
-
C.
Gregory S. Hubbard
Gregory S. Hubbard is an American individual known primarily for his involvement in a high-profile terrorism-related criminal case.
-
D.
Allen M. Davey
Allen M. Davey was an American cinematographer known for his work on early Technicolor films in Hollywood.
-
E.
Daniel L. Fapp
Daniel L. Fapp was an American cinematographer known for his work on numerous Hollywood films, including the Oscar-winning West Side Story.
- 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: David P. Haney Triple: [Hiram College, hasPresident, David P. Haney]
Generated description
David P. Haney is an American academic administrator who has served as president of Hiram College in Ohio.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David P. Haney Target entity description: David P. Haney is an American academic administrator who has served as president of Hiram College in Ohio.
-
A.
Eric L. Haney
Eric L. Haney is a former U.S. Army Delta Force operator and author known for his memoir "Inside Delta Force," which inspired the television series "The Unit."
-
B.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
-
C.
Gregory S. Hubbard
Gregory S. Hubbard is an American individual known primarily for his involvement in a high-profile terrorism-related criminal case.
-
D.
Allen M. Davey
Allen M. Davey was an American cinematographer known for his work on early Technicolor films in Hollywood.
-
E.
Daniel L. Fapp
Daniel L. Fapp was an American cinematographer known for his work on numerous Hollywood films, including the Oscar-winning West Side Story.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772ec55fc81909b2b15f2493dddc6 |
completed | April 9, 2026, 9:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af38e3548190a5192894932d9b1d |
completed | May 3, 2026, 2:13 a.m. |
| NEDg | Description generation | batch_69f6b02e3b9881909387c1f70176a1bd |
completed | May 3, 2026, 2:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6b11ced30819090f67a0b1e1369aa |
completed | May 3, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:24 p.m.