Triple
T13350061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1997 Phoenix Lights |
E318045
|
entity |
| Predicate | hasPhenomenonType |
P14526
|
FINISHED |
| Object | unidentified aerial phenomenon |
—
|
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: unidentified aerial phenomenon | Statement: [1997 Phoenix Lights, hasPhenomenonType, unidentified aerial phenomenon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhenomenonType Context triple: [1997 Phoenix Lights, hasPhenomenonType, unidentified aerial phenomenon]
-
A.
capturesPhenomenon
Indicates that one entity records, represents, or effectively reflects the occurrence or characteristics of a particular phenomenon.
-
B.
affectsPhenomenon
Indicates that one phenomenon produces an influence or change on another phenomenon.
-
C.
phenomenon
Indicates that an entity is a perceptible event, occurrence, or process that can be observed or experienced.
-
D.
demonstratedPhenomenon
Indicates that an entity has shown, exhibited, or provided evidence for the occurrence of a particular phenomenon.
-
E.
hasEventType
chosen
Indicates that an event is associated with, or classified under, a specific type or category of event.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.