Triple
T14319582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity Road Stand |
E355044
|
entity |
| Predicate | servesSupporterType |
P80302
|
FINISHED |
| Object | general admission supporters |
—
|
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: general admission supporters | Statement: [Trinity Road Stand, servesSupporterType, general admission supporters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesSupporterType Context triple: [Trinity Road Stand, servesSupporterType, general admission supporters]
-
A.
supporterType
Indicates the specific role or category of support a supporter provides in relation to another entity or activity.
-
B.
hasSupporter
Indicates that one entity supports, endorses, or backs another entity.
-
C.
associatedWithSupporters
Indicates that an entity has a relationship or connection with individuals or groups who support or advocate for it.
-
D.
supportersGroupType
chosen
Indicates the classification or category of a supporters group associated with an entity.
-
E.
typeOfSupport
Indicates the kind or category of assistance, help, or backing provided in a given context.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de883a93548190ac671b001d15d0bd |
completed | April 14, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:13 a.m.