Triple
T17207302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Sumatra |
E417632
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Pekanbaru |
E89869
|
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: Pekanbaru | Statement: [Central Sumatra, contains, Pekanbaru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pekanbaru Context triple: [Central Sumatra, contains, Pekanbaru]
-
A.
Pekanbaru
chosen
Pekanbaru is a major commercial and transportation hub in central Sumatra, Indonesia, known for its oil industry and rapid urban growth.
-
B.
Tanjung Pinang
Tanjung Pinang is a coastal city in Indonesia located on Bintan Island, known as an administrative and commercial hub in the Riau Islands province.
-
C.
Padang
Padang is a major coastal city in western Indonesia known as the capital of West Sumatra and a cultural and culinary center of the Minangkabau people.
-
D.
Batam
Batam is a major Indonesian industrial and transport hub located near Singapore, known for its free-trade zone status and rapidly growing economy.
-
E.
Pangkalpinang
Pangkalpinang is the largest city and administrative, economic, and cultural center of Indonesia’s Bangka Belitung Islands province, located on Bangka Island.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dc283648190b2c1f957940024aa |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01793aec4c81908e64226986866389 |
completed | May 11, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:38 a.m.