Triple
T5872138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA Member Associations |
E130539
|
entity |
| Predicate | typicalLegalForm |
P67327
|
FINISHED |
| Object | non‑profit association |
—
|
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: non‑profit association | Statement: [FIFA Member Associations, typicalLegalForm, non‑profit association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLegalForm Context triple: [FIFA Member Associations, typicalLegalForm, non‑profit association]
-
A.
legalForm
Indicates the specific legal structure or organizational type under which an entity is formally constituted and recognized by law.
-
B.
previousLegalForm
Indicates the legal form or organizational status an entity had before its current legal form.
-
C.
belongsToCompanyLegalForm
Indicates that an entity is associated with or classified under a specific legal form of a company.
-
D.
typicalForm
Indicates that one entity represents the standard, characteristic, or most common form or shape in which another entity typically appears or is realized.
-
E.
legalPersonality
Indicates that an entity possesses recognized legal status, enabling it to hold rights, bear obligations, and act as a subject under the law.
- F. None of above. chosen
Provenance (4 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c0432f06fc8190bc047d52ffc30d59 |
completed | March 22, 2026, 7:29 p.m. |
Created at: March 22, 2026, 3:56 p.m.