Triple
T17419397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pasaman Regency |
E423571
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Lubuk Sikaping |
—
|
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: Lubuk Sikaping | Statement: [Pasaman Regency, seat, Lubuk Sikaping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lubuk Sikaping Context triple: [Pasaman Regency, seat, Lubuk Sikaping]
-
A.
Lubuk Sikaping
chosen
Lubuk Sikaping is a town in West Sumatra, Indonesia, that serves as the administrative and economic center of Pasaman Regency.
-
B.
Lubuk Alung
Lubuk Alung is a town in West Sumatra, Indonesia, known as an important local administrative and transportation hub within Padang Pariaman Regency.
-
C.
Lubuk Basung
Lubuk Basung is the administrative and economic center of Agam Regency in West Sumatra, Indonesia.
-
D.
Gosong Rengat
Gosong Rengat is a small island area within Indonesia’s Thousand Islands Regency, known as part of the scattered archipelago off the coast of Jakarta.
-
E.
Muaro Sijunjung
Muaro Sijunjung is the main administrative and urban center of Sijunjung Regency in West Sumatra, Indonesia.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44236419c8190a106748bca6f30cd |
completed | April 19, 2026, 2:47 a.m. |
Created at: April 10, 2026, 5:46 a.m.