Triple
T4976742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koya language |
E111783
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Koya |
E175235
|
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: Koya | Statement: [Koya language, hasAlternativeName, Koya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koya Context triple: [Koya language, hasAlternativeName, Koya]
-
A.
Koya
chosen
Koya is a Dravidian language spoken primarily by the Koya tribal communities in parts of central and southern India.
-
B.
Koya town
Koya town is a historic settlement in Japan best known as the center of Shingon Buddhism and home to the sacred Mount Koya temple complex.
-
C.
Kuwahi
Kuwahi is the Cherokee name for Clingmans Dome, the highest peak in Great Smoky Mountains National Park and one of the tallest mountains in the eastern United States.
-
D.
Kurohime-yama
Kurohime-yama is a subsidiary peak of Japan’s Mount Akagi, known as part of the volcanic mountain’s multi-summit range in Gunma Prefecture.
-
E.
Kurohime-yama
Kurohime-yama is a mountain in Japan, known for its scenic landscapes and popular hiking and skiing opportunities.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7231448c8190a5d0a5135a9cfdf1 |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a0634b48190acb4a1834f5647cf |
completed | March 21, 2026, 12:07 p.m. |
Created at: March 20, 2026, 1:33 p.m.