Triple
T35137053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway production of Irma La Douce |
E1014601
|
entity |
| Predicate | roleOfIrmaPlayedBy |
P9616
|
FINISHED |
| Object | Elizabeth Seal |
—
|
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: Elizabeth Seal | Statement: [Broadway production of Irma La Douce, roleOfIrmaPlayedBy, Elizabeth Seal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfIrmaPlayedBy Context triple: [Broadway production of Irma La Douce, roleOfIrmaPlayedBy, Elizabeth Seal]
-
A.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
B.
characterPlayedByKathleenQuinlan
Indicates that a given character is portrayed or acted by Kathleen Quinlan.
-
C.
helenaBonhamCarterRole
Indicates the acting role or character portrayed by Helena Bonham Carter in a work.
-
D.
realPersonDepicted
Indicates that a real, actual person (not fictional or generic) is visually represented or shown in the subject entity.
-
E.
characterPlayedBy_MichelleRyan
Indicates that the subject is a character portrayed or played by Michelle Ryan.
- F. None of above.
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_69f76dd9c1848190af70d4882a2c1ad7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:02 p.m.