Triple
T6985184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kent Tekulve |
E161942
|
entity |
| Predicate | careerAppearances |
P66711
|
FINISHED |
| Object | 1050 |
—
|
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: 1050 | Statement: [Kent Tekulve, careerAppearances, 1050]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerAppearances Context triple: [Kent Tekulve, careerAppearances, 1050]
-
A.
clubAppearances
Indicates the number of official matches a player has played for a particular club.
-
B.
sportNumberOfAppearances
chosen
Indicates the total number of times an entity has participated in or appeared in a particular sport or sporting event.
-
C.
careerSeasons
Indicates the number or set of seasons during which an entity actively participated in a particular career or professional role.
-
D.
allStarAppearances
Indicates the number of times an entity has been selected to participate in an All-Star event or game.
-
E.
careerRuns
Indicates the total number of runs a player has scored over the entire duration of their professional career.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbbd926c8190a8b60527bd553fa3 |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.