Triple
T22538811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne Watanabe |
E557228
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Goemon (film) |
—
|
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: Goemon (film) | Statement: [Anne Watanabe, notableWork, Goemon (film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goemon (film) Context triple: [Anne Watanabe, notableWork, Goemon (film)]
-
A.
Goemon
chosen
Goemon is a 2009 Japanese period action film that reimagines the legendary outlaw Ishikawa Goemon as a stylish, larger-than-life hero in a fantasy-infused Sengoku-era setting.
-
B.
Go-Sees
Go-Sees is a photography book by Juergen Teller featuring candid, unvarnished portraits of aspiring fashion models visiting his studio.
-
C.
Gimojan
Gimojan is a subgroup of the Omotic language family spoken in southwestern Ethiopia.
-
D.
Mr Goon
Mr Goon is the bumbling, bad-tempered village policeman who frequently clashes with the child detectives in Enid Blyton’s Mystery Series.
-
E.
Goon
Goon is a 2011 sports comedy film in which Seann William Scott stars as a kind-hearted but tough enforcer on a minor league hockey team.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f302cd4819098c97ca4fa96363e |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.