Triple
T20370832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osric Chau |
E497046
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Arrow |
—
|
NE NERFINISHED |
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: Arrow | Statement: [Osric Chau, notableWork, Arrow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arrow Context triple: [Osric Chau, notableWork, Arrow]
-
A.
Arrow
Arrow is the nickname of the Avro Canada CF-105 Arrow, a Canadian supersonic interceptor aircraft developed in the 1950s.
-
B.
Arrow
chosen
Arrow is a popular American superhero television series based on the DC Comics character Green Arrow, known for launching the interconnected "Arrowverse" franchise.
-
C.
Arrow
Arrow is a regional passenger rail service brand used for trains operating between San Bernardino and Redlands in Southern California.
-
D.
Arrow
Arrow is a long-established American clothing brand best known for its men’s dress shirts and formalwear.
-
E.
Arrow
Arrow is the NATO reporting name for the German World War II heavy fighter aircraft Dornier Do 335 Pfeil, notable for its unique push-pull twin-engine configuration and exceptional speed.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678758b98819082c6440e03ad1615 |
completed | April 20, 2026, 7:03 p.m. |
Created at: April 16, 2026, 11:26 a.m.