Triple
T6783033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stalybridge Celtic F.C. |
E155730
|
entity |
| Predicate | hasGrassPitch |
P33887
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Stalybridge Celtic F.C., hasGrassPitch, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrassPitch Context triple: [Stalybridge Celtic F.C., hasGrassPitch, yes]
-
A.
hasGrassTypeGreens
Indicates that something possesses or includes green vegetation or grassy plant material.
-
B.
hasCricketGround
Indicates that one entity possesses, contains, or includes a cricket ground as part of its facilities or attributes.
-
C.
hasSportsGround
chosen
Indicates that an entity possesses, includes, or is associated with a sports ground or athletic field as part of its facilities or area.
-
D.
hasGrassSeatingArea
Indicates that an entity includes or provides a seating area located on a grass surface.
-
E.
hasTennisCourt
Indicates that one entity possesses, includes, or provides access to a tennis court as part of its facilities or attributes.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d289958481908ad4f9467a107083 |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:14 p.m.