Triple
T20753946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapanuli |
E510800
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Balige |
—
|
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: Balige | Statement: [Tapanuli, hasMajorTown, Balige]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Balige Context triple: [Tapanuli, hasMajorTown, Balige]
-
A.
Balige
chosen
Balige is a town in North Sumatra, Indonesia, known as an administrative and cultural center near Lake Toba.
-
B.
Cileunyi
Cileunyi is a suburban district on the eastern outskirts of Bandung in West Java, Indonesia, known as a growing residential and transit area within the Bandung metropolitan region.
-
C.
Gedebage
Gedebage is a district in the eastern part of Bandung, West Java, Indonesia, known for its growing urban development and strategic transport links.
-
D.
Nasinu
Nasinu is a major suburban town in Fiji, located between Suva and Nausori on the island of Viti Levu and known for being one of the country’s most populous municipalities.
-
E.
Amurang
Amurang is a coastal town in North Sulawesi, Indonesia, known as an administrative and economic center in the 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c22d0ebc8190b17077326f540f98 |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:34 p.m.