Triple
T19268663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wah-Wah |
E481856
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Senator 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: Senator Film | Statement: [Wah-Wah, productionCompany, Senator Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senator Film Context triple: [Wah-Wah, productionCompany, Senator Film]
-
A.
Senator Film
chosen
Senator Film is a German film distribution company known for releasing a wide range of domestic and international movies in German-speaking markets.
-
B.
The Senator
The Senator is a character from the video game "Black Water," likely serving as a prominent political figure within the game's narrative.
-
C.
The Director
The Director is a novel by British author John Gardner that explores the intrigues and power struggles within the world of theatre and film production.
-
D.
Lea Film
Lea Film was an Italian film production company active during the mid-20th century, known for contributing to genre cinema including giallo and thriller films.
-
E.
Mr. Director
Mr. Director is the formal style of address used for the Cabinet-level head of the United States Office of Management and Budget.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbb68d0c819083ba0ce680dd7d99 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:29 p.m.