Triple
T36749369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat and Margaret |
E907861
|
entity |
| Predicate | plotSummary |
P264
|
FINISHED |
| Object | The film follows the reunion of two estranged sisters whose very different lives collide when one becomes a famous TV personality. |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: The film follows the reunion of two estranged sisters whose very different lives collide when one becomes a famous TV personality. | Statement: [Pat and Margaret, plotSummary, The film follows the reunion of two estranged sisters whose very different lives collide when one becomes a famous TV personality.]
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_69f76e76d10881909ec1679bc043108c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9416a588190a04d4f6bf6077c1e |
completed | May 3, 2026, 10:16 p.m. |
Created at: May 3, 2026, 4:12 p.m.