Triple
T21179496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Kuta District |
E521906
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Kuta District |
—
|
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: Kuta District | Statement: [North Kuta District, adjacentTo, Kuta District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuta District Context triple: [North Kuta District, adjacentTo, Kuta District]
-
A.
Kuta District
chosen
Kuta District is a popular coastal area in southern Bali, Indonesia, known for its busy tourist beaches, nightlife, and surf culture.
-
B.
Buka District
Buka District is an administrative district located within the Tashkent Region of Uzbekistan.
-
C.
Nawa District
Nawa District is an administrative district in Ghazni Province, Afghanistan, known for its rural communities and location in the southeastern part of the country.
-
D.
Kasa District
Kasa District was a former rural administrative district located in Kyoto Prefecture, Japan, known for its small towns and villages before being dissolved through municipal mergers.
-
E.
Nooken District
Nooken District is an administrative district in southwestern Kyrgyzstan, located within the Jalal-Abad Region.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7301c842c8190b969a8b3f194003a |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 3:01 p.m.