Triple
T30764131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asseco Resovia |
E783316
|
entity |
| Predicate | hasSectionInMultiSportClub |
P37078
|
FINISHED |
| Object | Resovia sports association |
—
|
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: Resovia sports association | Statement: [Asseco Resovia, hasSectionInMultiSportClub, Resovia sports association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionInMultiSportClub Context triple: [Asseco Resovia, hasSectionInMultiSportClub, Resovia sports association]
-
A.
hasMultiClubNetwork
Indicates that an entity is part of, or associated with, a network comprising multiple clubs under common ownership, management, or affiliation.
-
B.
hasClub
Indicates that an entity is associated with or belongs to a particular club.
-
C.
hasFutsalSection
Indicates that an organization or club includes a dedicated futsal section or department as part of its structure.
-
D.
hasSectionIn
chosen
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
E.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
- 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_69f224b047f48190b4f5efeb7ee97b37 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: April 29, 2026, 8:39 p.m.