Triple
T17012415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come What May |
E412732
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Craig Armstrong |
E48032
|
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: Craig Armstrong | Statement: [Come What May, producer, Craig Armstrong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Armstrong Context triple: [Come What May, producer, Craig Armstrong]
-
A.
Craig Armstrong
chosen
Craig Armstrong is a Scottish composer and arranger renowned for his emotive film scores and orchestral works, including music for major films such as "Love Actually," "Moulin Rouge!" and "The Great Gatsby."
-
B.
Craig Armstrong
Craig Armstrong is a television producer best known for his work as an executive producer on popular reality and home-renovation series.
-
C.
Scot Armstrong
Scot Armstrong is an American screenwriter and producer known for his work on hit comedy films such as "Old School," "Road Trip," and "The Hangover Part II."
-
D.
David Armstrong
David Armstrong is a relatively common personal name shared by various individuals across fields such as sports, academia, and the arts.
-
E.
Scott Armstrong
Scott Armstrong is an American journalist and author known for his investigative reporting and coauthoring influential books on U.S. government and the Supreme Court.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d47cc17c819087f7bd27582bcbfa |
completed | April 18, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b4990948190861ff81f8fc3e8f2 |
completed | May 10, 2026, 11:56 p.m. |
Created at: April 10, 2026, 5:33 a.m.