Triple
T13684641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selorejo Dam |
E328090
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Kepanjen |
E654738
|
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: Kepanjen | Statement: [Selorejo Dam, locatedNear, Kepanjen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kepanjen Context triple: [Selorejo Dam, locatedNear, Kepanjen]
-
A.
Kepanjen
chosen
Kepanjen is a town in East Java, Indonesia, known as an administrative and growing urban center within the Malang region.
-
B.
Purbalingga
Purbalingga is a regency and its capital town in Central Java, Indonesia, known for its manufacturing industries and proximity to mountainous tourist areas.
-
C.
Nganjuk
Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
-
D.
Citeureup
Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
-
E.
Trenggalek
Trenggalek is a regency and its capital town in southern East Java, Indonesia, known for its coastal landscapes, caves, and agricultural economy.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc66f8acc8190b2a82b722930b995 |
completed | April 12, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b063661481908da569084c20f37c |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 9:53 p.m.