Triple
T25906856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igby Goes Down |
E652772
|
entity |
| Predicate | supportingActressNominationRecipient |
P31998
|
FINISHED |
| Object | Susan Sarandon |
—
|
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: Susan Sarandon | Statement: [Igby Goes Down, supportingActressNominationRecipient, Susan Sarandon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportingActressNominationRecipient Context triple: [Igby Goes Down, supportingActressNominationRecipient, Susan Sarandon]
-
A.
supportingActressNominee
chosen
Indicates that a person has been nominated for an award in the category of supporting actress.
-
B.
supportingActorNominee
Indicates that an entity has been nominated for an award recognizing their performance in a supporting acting role.
-
C.
supportingActorAwardRecipient
Indicates that an entity has received an award specifically for a supporting acting role in a performance or production.
-
D.
supportingActressRole
Indicates that an actress performs a supporting (non-leading) role in a particular production or work.
-
E.
leadingActressNominee
Indicates that a person has been nominated for an award in the leading actress category for a particular work or performance.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 22, 2026, 8:27 a.m.