Triple
T12688603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Dakota Coyotes |
E303142
|
entity |
| Predicate | varsitySportsGender |
P7453
|
FINISHED |
| Object | men's |
—
|
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: men's | Statement: [South Dakota Coyotes, varsitySportsGender, men's]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: varsitySportsGender Context triple: [South Dakota Coyotes, varsitySportsGender, men's]
-
A.
genderOfMascot
Indicates the gender associated with a particular mascot.
-
B.
sportGender
chosen
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
C.
parentClubGender
Indicates the gender category (e.g., men’s, women’s, mixed) associated with the parent club in a club–team or club–division relationship.
-
D.
hasGenderedTeams
Indicates that the entity organizes or participates in teams that are separated or defined based on gender.
-
E.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d962a32c6481908ddaddae4ea267bf |
completed | April 10, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69d960be63f081908a5ef5ef17a311bf |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:21 p.m.