Triple
T5600785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WNBA All-Star Game |
E147112
|
entity |
| Predicate | hasFanActivities |
P18289
|
FINISHED |
| Object | fan fest events |
—
|
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: fan fest events | Statement: [WNBA All-Star Game, hasFanActivities, fan fest events]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFanActivities Context triple: [WNBA All-Star Game, hasFanActivities, fan fest events]
-
A.
hasFanActivity
chosen
Indicates that an entity is associated with actions, behaviors, or engagement carried out by fans in relation to it.
-
B.
hasFanPerformances
Indicates that an entity has associated performances created or carried out by fans.
-
C.
hasFanCommunity
Indicates that an entity is associated with a group of fans who actively follow, support, or engage around it.
-
D.
hasFan
Indicates that an entity is the admirer, supporter, or enthusiast of another entity.
-
E.
hasPopularActivity
Indicates that an entity is associated with an activity that is widely favored, frequently engaged in, or well-liked by many people.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020da519c81908626b243e40db263 |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1890ec8190b9e6fa488792e4d4 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.