Triple
T36749383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat and Margaret |
E907861
|
entity |
| Predicate | starredJulieWaltersAs |
P186544
|
FINISHED |
| Object | Margaret |
—
|
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: Margaret | Statement: [Pat and Margaret, starredJulieWaltersAs, Margaret]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starredJulieWaltersAs Context triple: [Pat and Margaret, starredJulieWaltersAs, Margaret]
-
A.
starredActorWith
Indicates that one entity participated as an actor in a production together with another specified actor.
-
B.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
C.
starredAustralianActress
Indicates that a person performed a starring role as an actress in an Australian production.
-
D.
supportingActorAwardRecipient
Indicates that an entity has received an award specifically for a supporting acting role in a performance or production.
-
E.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
- F. None of above. chosen
Provenance (4 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_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:12 p.m.