Triple
T1095425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayr United F.C. |
E24259
|
entity |
| Predicate | hasNicknameOrigin |
P7596
|
FINISHED |
| Object | town of Ayr being known as the "Honest Toun" |
—
|
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: town of Ayr being known as the "Honest Toun" | Statement: [Ayr United F.C., hasNicknameOrigin, town of Ayr being known as the "Honest Toun"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNicknameOrigin Context triple: [Ayr United F.C., hasNicknameOrigin, town of Ayr being known as the "Honest Toun"]
-
A.
hasNameOrigin
Indicates that the origin or source of an entity’s name is specified by the related entity.
-
B.
hasAcronymOrigin
Indicates that an acronym is derived from or originates from a specific longer expression or name.
-
C.
reasonForNickname
chosen
Indicates the explanation or cause behind why a particular nickname was given to an entity.
-
D.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
E.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99e92308190b8a8c499e1630672 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.