Triple
T2840190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jackson State Tigers and Lady Tigers |
E62446
|
entity |
| Predicate | genderDesignation |
P974
|
FINISHED |
| Object | Tigers for men's teams |
—
|
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: Tigers for men's teams | Statement: [Jackson State Tigers and Lady Tigers, genderDesignation, Tigers for men's teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderDesignation Context triple: [Jackson State Tigers and Lady Tigers, genderDesignation, Tigers for men's teams]
-
A.
genderDivision
Indicates a relationship where roles, responsibilities, or categories are separated or distinguished based on gender.
-
B.
hasDesignation
chosen
Indicates that an entity holds or is assigned a specific title, label, or formal designation.
-
C.
designationType
Indicates the specific category or kind of formal status, title, or label that has been assigned in a designation relationship.
-
D.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
E.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf15b7288190a03d1193cc0544a6 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd0ce8b08190ba28c192988f38ce |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.