Triple
T14998523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siha District |
E374021
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object | Sanya Juu |
E1131053
|
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: Sanya Juu | Statement: [Siha District, administrativeCentre, Sanya Juu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanya Juu Context triple: [Siha District, administrativeCentre, Sanya Juu]
-
A.
Sanya Juu
chosen
Sanya Juu is a small town in northern Tanzania that serves as the administrative and commercial center of Siha District in the Kilimanjaro Region.
-
B.
Na San
Na San is a locality in northwestern Vietnam known primarily as the site of a major French defensive victory over the Viet Minh during the First Indochina War.
-
C.
Sanmu
Sanmu is a coastal city in Chiba Prefecture, Japan, known for its proximity to the Pacific Ocean and popular seaside areas.
-
D.
Hoan-ya
Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
-
E.
Fujinami
Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded71a5618819083ae96a79735ef98 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dcbd7c88190ad1a302cd0c6ef28 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:54 a.m.