Triple
T21449351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Moseley |
E529166
|
entity |
| Predicate | portrayed |
P1668
|
FINISHED |
| Object | Chop Top |
—
|
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: Chop Top | Statement: [Bill Moseley, portrayed, Chop Top]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chop Top Context triple: [Bill Moseley, portrayed, Chop Top]
-
A.
Chop Top
chosen
Chop Top is a deranged, metal-plated member of the cannibalistic Sawyer family and one of the primary antagonists in the horror film The Texas Chainsaw Massacre 2.
-
B.
Choppin
Choppin is a surname most notably associated with Gregory R. Choppin, an American chemist and co-discoverer of the element mendelevium.
-
C.
Chop Me Up
"Chop Me Up" is a hip hop- and R&B-influenced track from Justin Timberlake’s album FutureSex/LoveSounds, featuring guest verses by Three 6 Mafia and Timbaland.
-
D.
Curly Top
Curly Top is a 1935 musical film starring child actress Shirley Temple, known for its charming songs and Temple’s iconic performance.
-
E.
Chop Shop
Chop Shop is a critically acclaimed 2007 independent drama film set in Queens, New York, following a young boy working in an auto-body repair district, directed by Ramin Bahrani.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d11ca48190aafe25c97dfa5578 |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:06 p.m.