Triple
T16355444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gateway Football Conference |
E397166
|
entity |
| Predicate | sponsoredGender |
P123094
|
FINISHED |
| Object | men's sports |
—
|
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 sports | Statement: [Gateway Football Conference, sponsoredGender, men's sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsoredGender Context triple: [Gateway Football Conference, sponsoredGender, men's sports]
-
A.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
-
B.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
-
C.
plugGender
Indicates that one entity’s connector has a specified gender (e.g., male, female, neutral) in relation to another connector or interface.
-
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.
genderCustom
Indicates that an entity has a user-specified or non-standard gender designation beyond predefined gender categories.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2face3a54819099418edd0eecc963 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.