Triple
T13952608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Merrick |
E335567
|
entity |
| Predicate | produced |
P490
|
FINISHED |
| Object | Irma La Douce |
E107741
|
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: Irma La Douce | Statement: [David Merrick, produced, Irma La Douce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irma La Douce Context triple: [David Merrick, produced, Irma La Douce]
-
A.
Irma la Douce
chosen
Irma la Douce is a 1963 romantic comedy film starring Jack Lemmon and Shirley MacLaine, adapted from the French stage musical of the same name.
-
B.
Marlene
Marlene is a German biographical film directed by Joseph Vilsmaier about the life and career of actress and singer Marlene Dietrich.
-
C.
Marlene
Marlene is an energetic and friendly otter who appears as a main supporting character in the animated series "The Penguins of Madagascar."
-
D.
Edie
Edie is a 2017 British drama film starring Sheila Hancock as an elderly woman who embarks on a life-changing mountain-climbing adventure in the Scottish Highlands.
-
E.
Edie
Edie is a feminine given name, often used as a diminutive of names like Edwina or Edith.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e146720819085d0f5eae558b7a4 |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1cea88081908c37836447410b97 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:17 p.m.