Triple
T28316072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Unmarried Woman |
E717137
|
entity |
| Predicate | actressNominatedForOscar |
P76890
|
FINISHED |
| Object | Jill Clayburgh |
—
|
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: Jill Clayburgh | Statement: [An Unmarried Woman, actressNominatedForOscar, Jill Clayburgh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actressNominatedForOscar Context triple: [An Unmarried Woman, actressNominatedForOscar, Jill Clayburgh]
-
A.
academyAwardForBestActress
Indicates that an entity received the Academy Award for Best Actress in a leading role.
-
B.
leadingActressNominee
chosen
Indicates that a person has been nominated for an award in the leading actress category for a particular work or performance.
-
C.
numberOfAcademyAwardsForBestActress
Indicates the total count of Academy Awards received by an entity specifically in the Best Actress category.
-
D.
academyAwardNominations
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
-
E.
academyAwardWinningPerformances
Indicates that the performances in question have won an Academy Award (Oscar) for acting.
- 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f644e5e3c8819092a5295a8c566930 |
completed | May 2, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 12:20 a.m.