Triple
T17346430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bentham Professor of Jurisprudence |
E421698
|
entity |
| Predicate | hasHeldBy |
P44019
|
FINISHED |
| Object | Scott Shapiro |
—
|
NE ONDG |
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: Scott Shapiro | Statement: [Bentham Professor of Jurisprudence, hasHeldBy, Scott Shapiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scott Shapiro Context triple: [Bentham Professor of Jurisprudence, hasHeldBy, Scott Shapiro]
-
A.
Mark Shapiro
Mark Shapiro is an American media executive and sports industry leader who serves as president and a top decision-maker at Endeavor Group Holdings.
-
B.
Craig Shapiro
Craig Shapiro is a television writer and producer best known for co-creating and showrunning series such as the sci-fi drama "Salvation."
-
C.
Greg Shapiro
Greg Shapiro is an American film producer best known for his Academy Award-winning work on "The Hurt Locker" and other notable independent and studio films.
-
D.
Avi Tuschman
Avi Tuschman is a political scientist and author known for his work on the evolutionary origins of political ideology and contributions to popular science and policy discussions.
-
E.
Dan Levine
Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
- 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: Scott Shapiro Triple: [Bentham Professor of Jurisprudence, hasHeldBy, Scott Shapiro]
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scott Shapiro Target entity description: Scott Shapiro is a prominent American legal philosopher and Yale Law School professor known for his influential work on legal positivism, jurisprudence, and the nature of legal systems.
-
A.
Mark Shapiro
Mark Shapiro is an American media executive and sports industry leader who serves as president and a top decision-maker at Endeavor Group Holdings.
-
B.
Craig Shapiro
Craig Shapiro is a television writer and producer best known for co-creating and showrunning series such as the sci-fi drama "Salvation."
-
C.
Greg Shapiro
Greg Shapiro is an American film producer best known for his Academy Award-winning work on "The Hurt Locker" and other notable independent and studio films.
-
D.
Avi Tuschman
Avi Tuschman is a political scientist and author known for his work on the evolutionary origins of political ideology and contributions to popular science and policy discussions.
-
E.
Dan Levine
Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
- F. None of above. chosen
Provenance (4 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a2923b48190a5d1abd3f535c59f |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0195546198819085804ec0b5b18040 |
completed | May 11, 2026, 8:37 a.m. |
| NEDg | Description generation | batch_6a01965807cc819088792a88b8a099d3 |
in_progress | May 11, 2026, 8:42 a.m. |
Created at: April 10, 2026, 5:44 a.m.