Triple
T30570313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garrett Wang |
E778104
|
entity |
| Predicate | characterTypeOftenPlays |
P138103
|
FINISHED |
| Object | Starfleet officer |
—
|
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: Starfleet officer | Statement: [Garrett Wang, characterTypeOftenPlays, Starfleet officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeOftenPlays Context triple: [Garrett Wang, characterTypeOftenPlays, Starfleet officer]
-
A.
isOftenPlayedBy
Indicates that one entity frequently performs, interprets, or executes another entity, such as a musician often playing a particular piece or instrument.
-
B.
isOftenPlayedFor
Indicates that one entity is frequently performed, used, or presented for the benefit, enjoyment, or experience of another entity.
-
C.
typicallyPlays
chosen
Indicates that an entity is most commonly or habitually associated with playing a particular role, instrument, position, or type of game.
-
D.
isOftenPlayed
Indicates that an entity is frequently engaged with or performed, typically more often than other comparable entities.
-
E.
playsAs
Indicates that one entity performs, portrays, or assumes the role, character, or persona of another entity.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdec5ffe088190ac5505f26c6cff18 |
completed | May 8, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69fdeae15f1c81908fc63fbc1b028d2e |
completed | May 8, 2026, 1:53 p.m. |
Created at: April 29, 2026, 8:22 p.m.