Triple
T20599478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harau Valley |
E506135
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Payakumbuh |
—
|
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: Payakumbuh | Statement: [Harau Valley, locatedNear, Payakumbuh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Payakumbuh Context triple: [Harau Valley, locatedNear, Payakumbuh]
-
A.
Payakumbuh
chosen
Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
-
B.
Parepare
Parepare is a coastal city and important port on the western coast of South Sulawesi, Indonesia.
-
C.
Pagar Alam
Pagar Alam is a highland city in southern Sumatra, Indonesia, known for its cool climate, tea plantations, and scenic mountain landscapes near Mount Dempo.
-
D.
Padang Panjang
Padang Panjang is a small highland city in West Sumatra, Indonesia, known for its Minangkabau cultural heritage and cool mountainous climate.
-
E.
Panji Saprang
Panji Saprang is a figure from Javanese legend associated with the mytho-historical lineage surrounding Ken Angrok, the founder of the Singhasari kingdom.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1ef9ac8190b05e23c149529cb9 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:40 a.m.