Triple
T22300440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Unebi |
E551238
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Unebi-yama |
—
|
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: Unebi-yama | Statement: [Mount Unebi, hasAlternativeName, Unebi-yama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unebi-yama Context triple: [Mount Unebi, hasAlternativeName, Unebi-yama]
-
A.
Unebi-yama
chosen
Unebi-yama is a small, historically significant mountain in Kashihara, Nara Prefecture, traditionally regarded as one of the "Yamato Sanzan" and associated with early Japanese imperial history.
-
B.
Gembu
Gembu is a town located on the Mambilla Plateau in Taraba State, eastern Nigeria, known for its cool climate and scenic highland landscapes.
-
C.
Matora
Matora is a significant literary work by Slovak national revivalist Michal Miloslav Hodža, reflecting his cultural and linguistic efforts in the 19th century.
-
D.
Hatsu-uma
Hatsu-uma is a traditional Japanese festival day in early February dedicated to the deity Inari, marked by shrine visits and rituals for prosperity and good harvests.
-
E.
Hebi
Hebi is a prefecture-level city in northern Henan Province, China, known for its coal resources and developing industrial base.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1572399148190853c4e91fcf9f38c |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:41 p.m.