Triple
T19270509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Nevada yellow-legged frog |
E481910
|
entity |
| Predicate | order |
P568
|
FINISHED |
| Object | Anura |
—
|
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: Anura | Statement: [Sierra Nevada yellow-legged frog, order, Anura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anura Context triple: [Sierra Nevada yellow-legged frog, order, Anura]
-
A.
Anura
Anura is a masculine given name commonly used in Sri Lanka and other South Asian countries.
-
B.
Anura
chosen
Anura is the biological order of amphibians commonly known as frogs and toads, characterized by their tailless bodies, long hind limbs, and typically jumping locomotion.
-
C.
Garsaura
Garsaura was an ancient settlement in central Anatolia, known as the historical predecessor of the modern Turkish city of Aksaray.
-
D.
Aruni
Aruni is a revered Vedic sage known for his wisdom and role as a teacher in ancient Indian scriptures.
-
E.
Nalini
Nalini is an Indian senior advocate and prominent lawyer, best known for her work in constitutional and criminal law and for being the wife of former Finance Minister P. Chidambaram.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbb74ec48190a58d96b4b5b9af00 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:29 p.m.