Triple
T3854701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esquire |
E85384
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Arnold Gingrich
Arnold Gingrich was an American magazine editor best known as a co-founder and longtime editor of the influential men's magazine Esquire.
|
E392579
|
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: Arnold Gingrich | Statement: [Esquire, foundedBy, Arnold Gingrich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnold Gingrich Context triple: [Esquire, foundedBy, Arnold Gingrich]
-
A.
Milton Moore
Milton Moore was a cinematographer active during the silent film era, known for his work on early American cinema.
-
B.
Tucker Quayle
Tucker Quayle is the son of former U.S. Vice President Dan Quayle and a member of the prominent Quayle political family.
-
C.
Don Roberts
Don Roberts is a software engineer and author known for his contributions to object-oriented design and refactoring, including work on the influential book "Refactoring: Improving the Design of Existing Code."
-
D.
John W. Regan
John W. Regan was the husband of American silent film actress Helene Costello.
-
E.
Jeff Buchanan
Jeff Buchanan is a professional editor, likely working in publishing or media, known for collaborating on written content such as articles or manuscripts.
- 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: Arnold Gingrich Triple: [Esquire, foundedBy, Arnold Gingrich]
Generated description
Arnold Gingrich was an American magazine editor best known as a co-founder and longtime editor of the influential men's magazine Esquire.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arnold Gingrich Target entity description: Arnold Gingrich was an American magazine editor best known as a co-founder and longtime editor of the influential men's magazine Esquire.
-
A.
Milton Moore
Milton Moore was a cinematographer active during the silent film era, known for his work on early American cinema.
-
B.
Tucker Quayle
Tucker Quayle is the son of former U.S. Vice President Dan Quayle and a member of the prominent Quayle political family.
-
C.
Don Roberts
Don Roberts is a software engineer and author known for his contributions to object-oriented design and refactoring, including work on the influential book "Refactoring: Improving the Design of Existing Code."
-
D.
John W. Regan
John W. Regan was the husband of American silent film actress Helene Costello.
-
E.
Jeff Buchanan
Jeff Buchanan is a professional editor, likely working in publishing or media, known for collaborating on written content such as articles or manuscripts.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec05ec4c8190bd5e5463163712dc |
completed | March 9, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5041c7250819093b2743afeb6e36c |
completed | March 14, 2026, 6:45 a.m. |
| NEDg | Description generation | batch_69b504c46dcc8190a9775c39e5c734a9 |
completed | March 14, 2026, 6:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b505742830819093a861bde17c03c0 |
completed | March 14, 2026, 6:51 a.m. |
Created at: March 9, 2026, 3:19 p.m.