Triple
T1601386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OFC |
E34399
|
entity |
| Predicate | hasMemberAssociationType |
P781
|
FINISHED |
| Object | national football 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: national football association | Statement: [OFC, hasMemberAssociationType, national football association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberAssociationType Context triple: [OFC, hasMemberAssociationType, national football association]
-
A.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
B.
hasAssociateMember
Indicates that an entity has another entity connected to it in a non-full, typically limited or secondary, membership capacity.
-
C.
hasAffiliationType
chosen
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
D.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
-
E.
hasMemberFrom
Indicates that a group, organization, or collection includes at least one member originating from or belonging to a specified source, place, or category.
- 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a95b02cd448190be8e3db9a5a7bac0 |
completed | March 5, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69a907c1cad08190b9728dd557f39aa0 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.