Triple
T13412877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luwu Regency |
E320133
|
entity |
| Predicate | formerCapital |
P3417
|
FINISHED |
| Object | Palopo |
E318743
|
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: Palopo | Statement: [Luwu Regency, formerCapital, Palopo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palopo Context triple: [Luwu Regency, formerCapital, Palopo]
-
A.
Palopo
chosen
Palopo is a coastal city in Indonesia known as an important regional center in the province of South Sulawesi.
-
B.
Kendari
Kendari is the capital and largest city of Southeast Sulawesi Province on the Indonesian island of Sulawesi, known as a regional center for trade and maritime activities.
-
C.
Tondano
Tondano is a town in North Sulawesi, Indonesia, known as an administrative and cultural center of the Minahasa region near Lake Tondano.
-
D.
Parepare
Parepare is a coastal city and important port on the western coast of South Sulawesi, Indonesia.
-
E.
Kotamobagu
Kotamobagu is a city in North Sulawesi, Indonesia, known as an administrative and economic center in the Bolaang Mongondow region.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb556948190af008c88e5bbf051 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b05a6d808190bae503b177816718 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 9:35 p.m.