Triple
T11574720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shrek the Third |
E274473
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | John H. Williams |
E463832
|
NE FINISHED |
How this triple was built (2 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: John H. Williams | Statement: [Shrek the Third, producer, John H. Williams]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John H. Williams Context triple: [Shrek the Third, producer, John H. Williams]
-
A.
John H. Williams
chosen
John H. Williams is a film producer best known for his work on major feature films, including the acclaimed drama "Seven Years in Tibet."
-
B.
Radford E. Morrow
Radford E. Morrow was a prominent local figure in Georgia whose significance to the community led to the city of Morrow being named in his honor.
-
C.
James W. Jones
James W. Jones is a distinguished scholar of psychology and religion, recognized for his influential work at the intersection of psychoanalysis, theology, and religious experience.
-
D.
Anthony H. Wilson
Anthony H. Wilson is a British computer scientist known for his contributions to programming language design and formal methods.
-
E.
Ronald J. Williams
Ronald J. Williams is a computer scientist known for his influential contributions to neural networks and machine learning, particularly in the development of backpropagation and reinforcement learning algorithms.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89048120c81908258f984711f7dd4 |
completed | April 10, 2026, 5:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f08f645c70819085c13b641deecb82 |
completed | April 28, 2026, 10:43 a.m. |
Created at: April 8, 2026, 9:38 p.m.