Triple
T15080110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geoffrey Lewis |
E380117
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Geoffrey Lewis |
E380117
|
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: Geoffrey Lewis | Statement: [Geoffrey Lewis, name, Geoffrey Lewis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geoffrey Lewis Context triple: [Geoffrey Lewis, name, Geoffrey Lewis]
-
A.
Geoffrey Lewis
chosen
Geoffrey Lewis was an American character actor known for his prolific film and television career, often appearing in Westerns and Clint Eastwood movies.
-
B.
Geoffrey Carey
Geoffrey Carey is an actor known for his role in the film "Esther Kahn."
-
C.
Geoffrey Dawson
Geoffrey Dawson was a British newspaper editor and influential public figure who notably served as editor of The Times during the early 20th century.
-
D.
Geoffrey Carroll
Geoffrey Carroll is the sinister artist and bigamist at the center of the 1947 film noir thriller "The Two Mrs. Carrolls."
-
E.
Martin Lancaster
Martin Lancaster is a video game writer best known for his work on major titles such as Batman: Arkham Knight.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff80008c88190840f94222f867478 |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec87ad03c8190b8a77e8eca9caf4d |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:03 a.m.