Triple
T7314304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Kawi |
E168170
|
entity |
| Predicate | isNear |
P350
|
FINISHED |
| Object | Batu |
E160348
|
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: Batu | Statement: [Mount Kawi, isNear, Batu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batu Context triple: [Mount Kawi, isNear, Batu]
-
A.
Batu
chosen
Batu is a highland city in East Java, Indonesia, known for its cool climate, mountain scenery, and popular tourist attractions such as theme parks and apple orchards.
-
B.
Batu Ferringhi
Batu Ferringhi is a popular beach resort area on the northern coast of Penang Island in Malaysia, known for its sandy beaches, seaside hotels, and vibrant night market.
-
C.
Batuan
Batuan is a small inland town on the Philippine island of Bohol, known as one of the main gateways to the famous Chocolate Hills.
-
D.
Buk
Buk is a Soviet-designed, medium-range, surface-to-air missile system widely used for air defense by several countries, including Ukraine.
-
E.
Kalkan
Kalkan is a picturesque seaside town on Turkey’s Mediterranean coast, known for its historic architecture, steep cobbled streets, and upscale tourism.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ec03a7248190beb1dec612725e5b |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e56f4aa0819096d955e2ce298299 |
completed | March 28, 2026, 2:27 p.m. |
Created at: March 27, 2026, 3:02 p.m.