Triple
T17323919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Counties East League |
E420633
|
entity |
| Predicate | featuresClubsType |
P79958
|
FINISHED |
| Object | semi-professional football clubs |
—
|
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: semi-professional football clubs | Statement: [Northern Counties East League, featuresClubsType, semi-professional football clubs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresClubsType Context triple: [Northern Counties East League, featuresClubsType, semi-professional football clubs]
-
A.
featuresClubs
Indicates that something includes or presents one or more clubs as part of its composition, content, or offering.
-
B.
featuresSwissClubs
Indicates that something includes or highlights Swiss clubs as part of its content, composition, or offering.
-
C.
featuresNISAClubs
Indicates that something includes or presents NISA clubs as part of its content, composition, or participants.
-
D.
featuresFranchise
Indicates that one entity includes or presents a particular franchise as part of its content, offering, or composition.
-
E.
featuresSemiProfessionalClubs
chosen
Indicates that the subject includes or hosts semi-professional clubs as part of its structure or offerings.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d0cf2481908a018593ef39fd18 |
completed | April 19, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.