Triple
T20444126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Allom |
E501471
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Rough Cutt |
—
|
NE NERFINISHED |
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: Rough Cutt | Statement: [Tom Allom, workedWith, Rough Cutt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rough Cutt Context triple: [Tom Allom, workedWith, Rough Cutt]
-
A.
Rough Cutt
chosen
Rough Cutt is an American heavy metal band from the 1980s Los Angeles scene, known for its melodic yet hard-edged sound and connections to other prominent glam and metal acts.
-
B.
Rough Cut
Rough Cut is a 1980 crime-comedy film starring Burt Reynolds, Lesley-Anne Down, and David Niven, centered on a jewel heist in London.
-
C.
Cuttin Up
Cuttin Up is a breakout drill track by Chicago rapper Lud Foe that helped establish his aggressive, street-oriented style and grow his underground following.
-
D.
The Cut
The Cut is a street in the Waterloo area of London known for its theatres, restaurants, and proximity to major transport links.
-
E.
The Cut
The Cut is a digital publication and vertical of New York Magazine that focuses on fashion, culture, politics, and women’s issues.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfa7dd08190883a37e3480b152c |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.