Triple
T21263430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMC Hornet |
E524063
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Hornet |
—
|
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: Hornet | Statement: [AMC Hornet, alsoKnownAs, Hornet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hornet Context triple: [AMC Hornet, alsoKnownAs, Hornet]
-
A.
Hornet
Hornet is the stinging insect that serves as the fierce and energetic mascot for Alabama State University's athletic teams.
-
B.
Hornet
chosen
The hornet is a large, aggressive social wasp known for its powerful sting and distinctive buzzing flight.
-
C.
Hornisse
Hornisse is the German nickname given to the Messerschmitt Me 410, a World War II twin-engine heavy fighter and fast bomber used by the Luftwaffe.
-
D.
Wasp
Wasp is a Marvel Comics superheroine, founding member of the Avengers, known for her size-changing powers, bio-electric stings, and influential leadership within the team.
-
E.
Wasp
"Wasp" is an acclaimed 2003 British short film written and directed by Andrea Arnold, known for its gritty portrayal of a struggling single mother and for winning the Academy Award for Best Live Action Short Film.
- 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e9b2788190b834ba38367fb6c7 |
completed | April 21, 2026, 8:31 a.m. |
Created at: April 16, 2026, 4 p.m.