Triple
T27886888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FC Barcelona futsal team |
E705254
|
entity |
| Predicate | professionalSectionOf |
P71519
|
FINISHED |
| Object | FC Barcelona |
—
|
NE NERFINISHED |
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: FC Barcelona | Statement: [FC Barcelona futsal team, professionalSectionOf, FC Barcelona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalSectionOf Context triple: [FC Barcelona futsal team, professionalSectionOf, FC Barcelona]
-
A.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
B.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
C.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
-
D.
professionalName
Indicates the formal name or title an entity uses in a professional or occupational context.
-
E.
hasProfessionalSection
chosen
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
- 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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 27, 2026, 6:33 p.m.