Triple
T37125259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | That Kind of Woman |
E919371
|
entity |
| Predicate | leadActorForCharacterKay |
P191621
|
FINISHED |
| Object | Sophia Loren |
—
|
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: Sophia Loren | Statement: [That Kind of Woman, leadActorForCharacterKay, Sophia Loren]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorForCharacterKay Context triple: [That Kind of Woman, leadActorForCharacterKay, Sophia Loren]
-
A.
leadActorForCharacterJayWilliams
Indicates that a person is the primary actor portraying the character Jay Williams in a performance or production.
-
B.
leadRoleActor
Indicates that an actor performs a leading or principal role in a work or production.
-
C.
leadActorForCharacter Steel
Indicates that the specified person is the primary actor portraying the character Steel.
-
D.
leadActorRolePattern
Indicates a recurring or characteristic type of role that an actor typically plays as a leading performer in productions.
-
E.
leadActorForCharacterJade
Indicates that the subject is the primary actor who portrays the character named Jade.
- 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_69f76e9d13e48190a108f7fbf80ff375 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
| PDg | Predicate description generation | batch_69fce28a74508190aab36551094e8226 |
completed | May 7, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.