Triple
T10290229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double X |
E241342
|
entity |
| Predicate | hasCareerOPS |
P17560
|
FINISHED |
| Object | .1.038 |
—
|
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: .1.038 | Statement: [Double X, hasCareerOPS, .1.038]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCareerOPS Context triple: [Double X, hasCareerOPS, .1.038]
-
A.
careerOPS
chosen
Indicates a relationship where an entity’s career on-base plus slugging (OPS) statistic is recorded or associated with that entity.
-
B.
careerOPSPlus
Indicates a relationship where an entity’s career performance or opportunities are enhanced, improved, or positively adjusted beyond a standard or baseline level.
-
C.
hasCareerService
Indicates that an entity provides or is associated with a career-related support or advisory service for another entity.
-
D.
hasCareerSpanCoverage
Indicates that one entity’s coverage, record, or data extends across the full duration of another entity’s career span.
-
E.
hasCareerTrack
Indicates that an entity is associated with or follows a particular career path or professional progression.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:41 a.m.