Triple
T6206080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikuma River |
E138749
|
entity |
| Predicate | isTouristAttractionIn |
P7335
|
FINISHED |
| Object | Hita |
E576165
|
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: Hita | Statement: [Mikuma River, isTouristAttractionIn, Hita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hita Context triple: [Mikuma River, isTouristAttractionIn, Hita]
-
A.
Hita
chosen
Hita is a historic city in Ōita Prefecture on Japan’s Kyushu island, known for its preserved traditional townscape, riverside setting, and summer festivals.
-
B.
Hagi
Hagi is a historic castle town in Yamaguchi Prefecture, Japan, known for its well-preserved samurai districts, traditional streets, and role in the late Edo and Meiji Restoration periods.
-
C.
Hatta
Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
-
D.
Hakitia
Hakitia is a Judeo-Spanish dialect historically spoken by North African Sephardic Jews, blending Old Spanish with Hebrew and elements of Arabic.
-
E.
Hagonoy
Hagonoy is a coastal municipality in the province of Bulacan in the Philippines, known for its fishing industry and aquaculture.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626f85748190a94448117a85fd78 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d9def0481909dc252d8a0ace45e |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:20 p.m.