Triple
T35669526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeffrey Gardiner |
E1030671
|
entity |
| Predicate | gameStyleSpecialty |
P51957
|
FINISHED |
| Object | open-world games |
—
|
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: open-world games | Statement: [Jeffrey Gardiner, gameStyleSpecialty, open-world games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameStyleSpecialty Context triple: [Jeffrey Gardiner, gameStyleSpecialty, open-world games]
-
A.
styleSpecialty
chosen
Indicates a relationship where an entity’s expertise, focus, or specialization is in a particular style or stylistic approach.
-
B.
teamSpecialty
Indicates the particular area of expertise or focus that characterizes a team’s skills or activities.
-
C.
teamEventSpecialty
Indicates that a team event is associated with a particular specialty, discipline, or specific type of competitive focus.
-
D.
styleOfPlay
Indicates the characteristic manner or approach in which an entity performs or behaves, especially in a game, sport, or artistic context.
-
E.
uniformSpecialty
Indicates that multiple entities share the same specific specialty, expertise, or area of focus.
- 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79fb10c4881908b12bfceaaf085f1 |
completed | May 3, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.