Triple
T33475467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Tech Bears |
E857308
|
entity |
| Predicate | sportStatus |
P22493
|
FINISHED |
| Object | intercollegiate varsity |
—
|
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: intercollegiate varsity | Statement: [New York Tech Bears, sportStatus, intercollegiate varsity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportStatus Context triple: [New York Tech Bears, sportStatus, intercollegiate varsity]
-
A.
sportingStatus
Indicates the competitive or professional sports-related standing or condition associated with an entity.
-
B.
sportsCountStatus
Indicates the status or condition of how many sports-related items or activities are present or counted.
-
C.
competitionStatus
Indicates the current state or phase of a competition, such as whether it is upcoming, ongoing, paused, or completed.
-
D.
sportContested
Indicates that a particular sport is actively played, competed in, or held as an event between participants or teams.
-
E.
hasSportsStatus
chosen
Indicates that an entity holds a particular sports-related status, role, or classification (such as amateur, professional, active, or retired) within a sporting context.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:38 a.m.