Triple
T14393849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Kleinberg |
E356907
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object |
David Easley
David Easley is an American economist and Cornell University professor known for his influential work in financial economics, market microstructure, and the economics of information.
|
E1096539
|
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 Easley | Statement: [Jon Kleinberg, coAuthor, David Easley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Easley Context triple: [Jon Kleinberg, coAuthor, David Easley]
-
A.
Brandon S. Rogers
Brandon S. Rogers is a writer best known for his work on the film "Long Distance."
-
B.
Derek R. Hill
Derek R. Hill was a distinguished British production designer and art director known for his work on notable films including "Heaven & Earth."
-
C.
Jason M. Frierson
Jason M. Frierson is an American attorney and former Nevada Assembly Speaker who serves as the United States Attorney for the District of Nevada.
-
D.
Blake R. Beeson
Blake R. Beeson is a film editor known for his work on the science-fiction movie "After Earth."
-
E.
Eric Danchick
Eric Danchick is a film producer known for his work on the movie "Bound 2."
- 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 Easley Triple: [Jon Kleinberg, coAuthor, David Easley]
Generated description
David Easley is an American economist and Cornell University professor known for his influential work in financial economics, market microstructure, and the economics of information.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Easley Target entity description: David Easley is an American economist and Cornell University professor known for his influential work in financial economics, market microstructure, and the economics of information.
-
A.
Brandon S. Rogers
Brandon S. Rogers is a writer best known for his work on the film "Long Distance."
-
B.
Derek R. Hill
Derek R. Hill was a distinguished British production designer and art director known for his work on notable films including "Heaven & Earth."
-
C.
Jason M. Frierson
Jason M. Frierson is an American attorney and former Nevada Assembly Speaker who serves as the United States Attorney for the District of Nevada.
-
D.
Blake R. Beeson
Blake R. Beeson is a film editor known for his work on the science-fiction movie "After Earth."
-
E.
Eric Danchick
Eric Danchick is a film producer known for his work on the movie "Bound 2."
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de902d114881908a8f3c01b3c6d309 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551b006c8190b84449f2e2b59b62 |
completed | May 8, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69fd55d90ed08190b6a0184715f39ff4 |
completed | May 8, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd565d32fc8190acc1e733537a23cb |
completed | May 8, 2026, 3:19 a.m. |
Created at: April 10, 2026, 1:16 a.m.