Triple
T13958164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barru Regency |
E335720
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Barru |
E1071373
|
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: Barru | Statement: [Barru Regency, seat, Barru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barru Context triple: [Barru Regency, seat, Barru]
-
A.
Barru
chosen
Barru is a coastal town in South Sulawesi, Indonesia, known as an administrative and economic center in the region.
-
B.
Maicao
Maicao is a Colombian border city in the northeastern La Guajira region, known as a major commercial hub with significant Arab and Wayuu indigenous communities.
-
C.
Yapeyú
Yapeyú is a small town in northeastern Argentina, historically notable as the birthplace of independence leader José de San Martín.
-
D.
Nipomo
Nipomo is a small unincorporated community in California’s Central Coast region, known for its agricultural roots and proximity to the Pacific Ocean in southern San Luis Obispo County.
-
E.
Caucaia
Caucaia is a coastal municipality in northeastern Brazil known for its beaches and proximity to the state capital, Fortaleza.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7a34f08190aa0d88b66154f268 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac8c06ec8190a6dfceab55da5b30 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:17 p.m.