Triple
T726656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Kevin Walker |
E14739
|
entity |
| Predicate | wroteScreenplayFor |
P15305
|
FINISHED |
| Object | 8MM |
E86275
|
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: 8MM | Statement: [Andrew Kevin Walker, wroteScreenplayFor, 8MM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 8MM Context triple: [Andrew Kevin Walker, wroteScreenplayFor, 8MM]
-
A.
8MM
chosen
8MM is a 1999 neo-noir crime thriller film starring Nicolas Cage as a private investigator drawn into the dark underworld of illegal pornography.
-
B.
M8
M8 is a major motorway in Scotland that connects the cities of Glasgow and Edinburgh.
-
C.
BB-63
BB-63 is the hull number of USS Missouri, a famous Iowa-class battleship best known as the site of Japan’s formal surrender in World War II.
-
D.
BB-36
BB-36 is the hull classification symbol for USS Nevada, a U.S. Navy battleship notable for its service during both World Wars and survival of the Pearl Harbor attack.
-
E.
BB-38
BB-38 is the hull number of USS Pennsylvania, a Pennsylvania-class battleship of the United States Navy that served prominently during both World Wars.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a9adf08190bf2baade7e2e1c1c |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a64a5c9d248190b0bebfd0e999643a |
completed | March 3, 2026, 2:41 a.m. |
Created at: March 1, 2026, 7:37 p.m.