Triple
T27304147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF Tangmere |
E689001
|
entity |
| Predicate | recordSetAt |
P175222
|
FINISHED |
| Object | world air speed record by Neville Duke in 1953 |
—
|
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: world air speed record by Neville Duke in 1953 | Statement: [RAF Tangmere, recordSetAt, world air speed record by Neville Duke in 1953]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordSetAt Context triple: [RAF Tangmere, recordSetAt, world air speed record by Neville Duke in 1953]
-
A.
recordSetIn
Indicates that a record or recording is associated with, or took place in, a particular setting, location, or context.
-
B.
recordSetAgainst
Indicates that a performance, statistic, or benchmark was achieved in opposition to or during a specific event, opponent, or condition.
-
C.
setRecordFor
Indicates establishing or updating a specific record associated with an entity or context.
-
D.
recordSetInSeason
Indicates that a particular record or achievement was set during a specified sports season.
-
E.
recordsWith
Indicates that one entity keeps or maintains documented information about another entity or event.
- 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_69ef355b931c8190a63cafaf7bcc008b |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cee3604c81908a07eade2f39064e |
completed | May 3, 2026, 4:28 a.m. |
Created at: April 27, 2026, 11:23 a.m.