Triple
T10560805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scomberesocidae |
E249211
|
entity |
| Predicate | notableSpecies |
P965
|
FINISHED |
| Object | Cololabis saira |
E871502
|
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: Cololabis saira | Statement: [Scomberesocidae, notableSpecies, Cololabis saira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cololabis saira Context triple: [Scomberesocidae, notableSpecies, Cololabis saira]
-
A.
Cololabis
chosen
Cololabis is a genus of sauries, slender pelagic fishes found in temperate and tropical oceans.
-
B.
Kaolie
Kaolie was a monarch of the ancient Chinese state of Chu during the Warring States period, remembered primarily through historical records that preserve his posthumous title.
-
C.
Liotta
Liotta is an Italian-origin surname most famously associated with American actor Ray Liotta, known for his roles in films like "Goodfellas."
-
D.
Nasuella
Nasuella is a small genus of South American carnivorous mammals known as mountain coatis, characterized by their elongated snouts and arboreal habits.
-
E.
Collip
Collip is a surname most notably associated with James Collip, a Canadian biochemist who was part of the team that developed insulin as a treatment for diabetes.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5271f3c6c819080b49fbe3aa09e09 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b38b4c081908cc2816144c23152 |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:35 p.m.