Triple
T7628066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangerang people |
E172686
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Bangerang |
E638913
|
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: Bangerang | Statement: [Bangerang people, hasAlternativeName, Bangerang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangerang Context triple: [Bangerang people, hasAlternativeName, Bangerang]
-
A.
Bangerang
chosen
Bangerang are an Aboriginal Australian people traditionally associated with parts of northern Victoria and southern New South Wales, with a distinct language and cultural heritage.
-
B.
Kutoarjo
Kutoarjo is a town in Central Java, Indonesia, known as a regional transport hub and local commercial center.
-
C.
Kertawangi
Kertawangi is a village located in West Bandung Regency in the West Java province of Indonesia.
-
D.
Rangat
Rangat is a coastal town and administrative hub located on Middle Andaman Island in the Andaman and Nicobar Islands, India.
-
E.
Bolango-Bulango
Bolango-Bulango is an Austronesian language spoken by the Bolango people in northern Sulawesi, Indonesia.
- 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa831f508190ab2f72326cdf4497 |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870af222481909e341eebb78664d6 |
completed | March 29, 2026, 12:22 a.m. |
Created at: March 27, 2026, 3:56 p.m.