Triple
T23054416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nggela |
E574111
|
entity |
| Predicate | neighboringLanguage |
P16383
|
FINISHED |
| Object | Bugotu |
E147942
|
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: Bugotu | Statement: [Nggela, neighboringLanguage, Bugotu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bugotu Context triple: [Nggela, neighboringLanguage, Bugotu]
-
A.
Bugotu
chosen
Bugotu is an Austronesian language of the Meso-Melanesian subgroup spoken primarily on Santa Isabel Island in the Solomon Islands.
-
B.
Bungotakada
Bungotakada is a small coastal city in northeastern Kyushu, Japan, known for its preserved Showa-era townscape and scenic rural landscapes.
-
C.
Bunzo
Bunzo is the pet belonging to someone named Kumiko, likely a beloved animal companion in their household.
-
D.
Bungoono
Bungoono is a city located in southern Ōita Prefecture on Japan’s Kyushu island, known for its rural landscapes, hot springs, and historic stone Buddhas.
-
E.
Kotoden
Kotoden is a private Japanese railway company operating electric train services in Kagawa Prefecture, particularly around Takamatsu and Kotohira.
- 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_69e245ba7ae48190be606dbc54120e39 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1867eaed0819095c7da6b06101b12 |
completed | April 29, 2026, 4:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c0ae217848190a2ecc1d008786a74 |
completed | May 19, 2026, 7:01 a.m. |
Created at: April 17, 2026, 3:54 p.m.