Triple
T14075309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valiants |
E338715
|
entity |
| Predicate | fieldSport |
P1080
|
FINISHED |
| Object | soccer |
—
|
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: soccer | Statement: [Valiants, fieldSport, soccer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldSport Context triple: [Valiants, fieldSport, soccer]
-
A.
traditionalSport
Indicates that an entity is a sport practiced within a culture or community that has been passed down over generations and is recognized as part of traditional or heritage activities.
-
B.
sportsAndRecreation
Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
-
C.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
-
D.
sportFocus
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
E.
primarySport
chosen
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5cdd288190914e1d57321b3554 |
completed | April 14, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.