Triple
T10233240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudolf Nureyev |
E243395
|
entity |
| Predicate | defectionEvent |
P12199
|
FINISHED |
| Object | defection at Le Bourget Airport, Paris |
—
|
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: defection at Le Bourget Airport, Paris | Statement: [Rudolf Nureyev, defectionEvent, defection at Le Bourget Airport, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defectionEvent Context triple: [Rudolf Nureyev, defectionEvent, defection at Le Bourget Airport, Paris]
-
A.
defectedTo
chosen
Indicates that an entity abandoned its original side, group, or allegiance and joined or gave support to another, typically opposing, side.
-
B.
defectionYear
Indicates the year in which an entity defected or switched allegiance from one side, group, or affiliation to another.
-
C.
attemptedDefectionTo
Indicates an action where one party tried, but may not have succeeded, to leave or abandon their current side, group, or allegiance in order to join another specified party.
-
D.
afterDefectionTitle
Indicates that a title or designation is assigned to an entity specifically after it has defected from a previous affiliation or allegiance.
-
E.
placeOfMutiny
Indicates the location where a mutiny occurred or took place.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:20 a.m.