Triple
T1594945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia Big 5 |
E34257
|
entity |
| Predicate | genderFocusHistorically |
P2452
|
FINISHED |
| Object | men's basketball |
—
|
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 basketball | Statement: [Philadelphia Big 5, genderFocusHistorically, men's basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderFocusHistorically Context triple: [Philadelphia Big 5, genderFocusHistorically, men's basketball]
-
A.
hasGenderFocus
chosen
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
B.
historicallyDominatedBy
Indicates that one entity has exercised controlling power or authority over another entity during a past historical period.
-
C.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
D.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
E.
historicallyConsidered
Indicates that one entity has been regarded or classified in a particular way relative to another entity during a past historical period.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a916d413f08190a4e137e5ed262e25 |
completed | March 5, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69a907bfb39c8190a31e0be14d3d52e6 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.