Triple
T19031842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taryn Tkachuk |
E465758
|
entity |
| Predicate | primarySportSurface |
P110106
|
FINISHED |
| Object | field hockey pitch |
—
|
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: field hockey pitch | Statement: [Taryn Tkachuk, primarySportSurface, field hockey pitch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySportSurface Context triple: [Taryn Tkachuk, primarySportSurface, field hockey pitch]
-
A.
hasCourtSurface
chosen
Indicates that something (such as a court or playing area) possesses a specific type of surface.
-
B.
homeFieldSurface
Indicates the type of playing surface used at a team's home field or stadium.
-
C.
homeArenaSurface
Indicates the type of playing surface used in an entity’s home arena.
-
D.
outfieldSurface
Indicates the type or condition of the playing surface specifically in the outfield area of a sports field.
-
E.
primarySport
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d7410dd08190b08a7c0a2b8d67f3 |
completed | April 20, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69e4a3001e388190aa6057266514e75a |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.