Triple
T20329179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jo Eisinger |
E492423
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Gilda |
—
|
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: Gilda | Statement: [Jo Eisinger, notableWork, Gilda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilda Context triple: [Jo Eisinger, notableWork, Gilda]
-
A.
Gilda
chosen
Gilda is a classic 1946 American film noir starring Rita Hayworth in one of her most iconic roles.
-
B.
Gilda
Gilda is the witty, free-spirited woman at the center of Noël Coward’s play "Design for Living," entangled in a complex romantic triangle.
-
C.
Gilda
Gilda is the innocent and devoted daughter of the jester in Giuseppe Verdi’s opera "Rigoletto," whose tragic fate drives the drama’s emotional core.
-
D.
Johnny Guitar
Johnny Guitar is a 1954 cult-classic Western film, noted for its unconventional style, strong female lead, and subversive take on genre conventions.
-
E.
Murder, My Sweet
Murder, My Sweet is a 1944 film noir adaptation of Raymond Chandler’s novel "Farewell, My Lovely," noted for its hardboiled detective story and atmospheric style.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677e637e48190b5582e97fe1000c0 |
completed | April 20, 2026, 7 p.m. |
Created at: April 16, 2026, 11:22 a.m.