Triple
T6190137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romper Stomper |
E138164
|
entity |
| Predicate | hasEditor |
P1954
|
FINISHED |
| Object | Bill Murphy |
E138164
|
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: Bill Murphy | Statement: [Romper Stomper, hasEditor, Bill Murphy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Murphy Context triple: [Romper Stomper, hasEditor, Bill Murphy]
-
A.
Bill Murphy
chosen
Bill Murphy is a film editor known for his work on the Australian drama film "Romper Stomper."
-
B.
Mitch Martin
Mitch Martin is the hapless, newly single protagonist of the comedy film "Old School," whose midlife crisis leads him to start a wild fraternity with his friends.
-
C.
Robert Klein
Robert Klein is an American stand-up comedian and actor known for his influential role in modern observational comedy and numerous appearances on television and Broadway.
-
D.
Jon Tenney
Jon Tenney is an American actor best known for his role as FBI Special Agent Fritz Howard on the television crime drama series "The Closer."
-
E.
Max Borenstein
Max Borenstein is an American screenwriter and producer best known for his work on the modern Godzilla and MonsterVerse films.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0621abad48190acb9ec019c065ed4 |
completed | March 22, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f0d5a2881908564442aca29b1ec |
completed | March 23, 2026, 4:49 p.m. |
Created at: March 22, 2026, 4:19 p.m.