Triple
T5371480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Layer Road |
E108858
|
entity |
| Predicate | notableMatchType |
P48257
|
FINISHED |
| Object | FA Cup ties |
—
|
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: FA Cup ties | Statement: [Layer Road, notableMatchType, FA Cup ties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableMatchType Context triple: [Layer Road, notableMatchType, FA Cup ties]
-
A.
notableMatch
Indicates that there exists a particularly significant or noteworthy match or pairing between the related entities.
-
B.
featuredMatchType
chosen
Indicates the specific category or kind of match that is highlighted or given special prominence.
-
C.
notableMatchVenueFor
Indicates that a venue is notably associated with hosting a particular match or game.
-
D.
notablePlayType
Indicates that a particular type or category of play is especially significant or characteristic for the subject.
-
E.
notablePlay
Indicates that a particular play is especially famous, significant, or noteworthy in relation to the entity it is associated with.
- 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_69bd440c77948190aad2a5f39b7b80f5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd88801b188190b9ac35ed89167fa3 |
completed | March 20, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69bd846172788190969f24bc7503c05e |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.