Triple
T14527485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shan Yu |
E340816
|
entity |
| Predicate | pet |
P8711
|
FINISHED |
| Object | Falcon |
E76974
|
NE 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: Falcon | Statement: [Shan Yu, pet, Falcon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Falcon Context triple: [Shan Yu, pet, Falcon]
-
A.
Falcon
chosen
The Falcon is a bird of prey known for its exceptional speed, keen vision, and use in the sport of falconry.
-
B.
Falcon
Falcon is a Marvel Comics superhero and member of the Avengers, known for his advanced winged flight suit and partnership with Captain America.
-
C.
Falcon
Falcon is a family of large language models designed for high-performance text generation and widely used in open-source AI applications.
-
D.
Falcon
"Falcon" is a popular electronic dance music track by French DJ and producer Michael Calfan, known for its uplifting house style and melodic energy.
-
E.
Falcon
Falcon is the menacing peregrine falcon antagonist in the family film "Stuart Little 2."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea051bc608190ad4d516c5e7bca43 |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a52260881909a0d85603666107d |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.