Triple
T13349910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1947 Kenneth Arnold sighting |
E318042
|
entity |
| Predicate | hasTermOrigin |
P3325
|
FINISHED |
| Object | "flying saucer" |
—
|
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: "flying saucer" | Statement: [1947 Kenneth Arnold sighting, hasTermOrigin, "flying saucer"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTermOrigin Context triple: [1947 Kenneth Arnold sighting, hasTermOrigin, "flying saucer"]
-
A.
hasNameOrigin
chosen
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.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
D.
originatesAs
Indicates that one entity begins, arises, or comes into existence in the form, state, or role specified by another entity.
-
E.
hasOriginIn
Indicates that something begins, arises, or is derived from a specified source, place, or cause.
- 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.