Triple
T5207737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Arrows |
E117552
|
entity |
| Predicate | airShows |
P62023
|
FINISHED |
| Object | United Kingdom airshows |
—
|
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: United Kingdom airshows | Statement: [Black Arrows, airShows, United Kingdom airshows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airShows Context triple: [Black Arrows, airShows, United Kingdom airshows]
-
A.
shows
Indicates that one entity presents, displays, or makes another entity visible or known to an audience or observer.
-
B.
televisionShow
Indicates that one entity is a television show associated with, or featured in relation to, another entity.
-
C.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
-
D.
showsThat
Indicates that one entity demonstrates, proves, or provides evidence for the truth or validity of another.
-
E.
hostedShow
Indicates that one entity served as the host or presenter of a particular show or program involving the other entity.
- F. None of above. chosen
Provenance (4 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a6d70d081908c74e86b3bca9ba2 |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79000cf88190b3c05d95395b0cd2 |
completed | March 20, 2026, 4:42 p.m. |
Created at: March 20, 2026, 1:47 p.m.