Triple
T34709176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shin |
E1000589
|
entity |
| Predicate | voiceActorOccupation |
P152304
|
FINISHED |
| Object | actress |
—
|
LITERAL FINISHED |
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: actress | Statement: [Shin, voiceActorOccupation, actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voiceActorOccupation Context triple: [Shin, voiceActorOccupation, actress]
-
A.
voiceActorProfession
chosen
Indicates that the subject works or is recognized professionally as a voice actor.
-
B.
voiceActorOfPerformer
Indicates that one performer provides the voice for a character or role portrayed by another performer.
-
C.
leadActorOccupation
Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
-
D.
portrayedByProfession
Indicates that an entity is depicted or represented by someone acting in a specified professional capacity.
-
E.
portrayedProfessionOfCharacter
Indicates that one entity is the profession or occupation depicted as being held by a particular character.
- 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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 3:59 p.m.