Triple
T10812002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Tickets to London |
E255124
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | William Forrest |
E723488
|
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: William Forrest | Statement: [Two Tickets to London, castMember, William Forrest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Forrest Context triple: [Two Tickets to London, castMember, William Forrest]
-
A.
William Forrest
chosen
William Forrest was an American character actor known for his numerous supporting roles in mid-20th-century films and television.
-
B.
Robert Forrest
Robert Forrest is the husband of acclaimed American actress Gena Rowlands.
-
C.
Lafayette Reynolds
Lafayette Reynolds is a flamboyant, sharp-tongued short-order cook and medium on the HBO vampire drama series "True Blood."
-
D.
Broderick Fobbs
Broderick Fobbs is an American football coach best known for revitalizing Grambling State University's football program and leading the Tigers to multiple conference championships.
-
E.
Blackford Oakes
Blackford Oakes is a fictional American CIA agent and Cold War spy created by William F. Buckley Jr.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733eadda48190b2b1183ee60102cb |
completed | April 9, 2026, 5:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de853692f08190914cbeaf1a558730 |
completed | April 14, 2026, 6:19 p.m. |
Created at: April 8, 2026, 9:18 p.m.