Triple
T30398670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimberly Akimbo |
E773288
|
entity |
| Predicate | originalOffBroadwayCastLead |
P110092
|
FINISHED |
| Object | Victoria Clark |
—
|
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: Victoria Clark | Statement: [Kimberly Akimbo, originalOffBroadwayCastLead, Victoria Clark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalOffBroadwayCastLead Context triple: [Kimberly Akimbo, originalOffBroadwayCastLead, Victoria Clark]
-
A.
originalBroadwayCoStar
Indicates that two performers appeared together as co-stars in the original Broadway production of the same show.
-
B.
portrayedInOriginalOffBroadwayProductionBy
chosen
Indicates that an entity was depicted or played by a particular performer in the original Off-Broadway production of a work.
-
C.
portrayedInBroadwayProductionBy
Indicates that an entity was depicted or performed in a Broadway stage production by a specified person or group.
-
D.
originalBroadwayStar
Indicates that the subject was a member of the original Broadway cast in the specified role or production.
-
E.
broadwayLeadActor
Indicates that the subject is the principal or starring actor in a Broadway production associated with the object.
- 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_69f2248facd48190b183c3f3ca6daef7 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 |
completed | May 10, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_6a0038e525448190a4c815f51595e78d |
completed | May 10, 2026, 7:51 a.m. |
Created at: April 29, 2026, 8:03 p.m.