Triple
T4412773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cigar |
E94888
|
entity |
| Predicate | studCareer |
P55489
|
FINISHED |
| Object | stood at Ashford Stud in Kentucky |
—
|
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: stood at Ashford Stud in Kentucky | Statement: [Cigar, studCareer, stood at Ashford Stud in Kentucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studCareer Context triple: [Cigar, studCareer, stood at Ashford Stud in Kentucky]
-
A.
collegeCareerStart
Indicates the time or event at which an individual begins their college-level academic career.
-
B.
careerTackles
Indicates the total number of tackles a player has made over the course of their entire career.
-
C.
careerWalks
Indicates the total number of bases on balls (walks) a player has received over the course of their entire career.
-
D.
careerAssists
Indicates the total number of assists a player has recorded over the entire span of their professional or competitive career.
-
E.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
- F. None of above. chosen
Provenance (4 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e7b30c819082ee781dd202dcc4 |
completed | March 13, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:29 p.m.