Triple
T6244021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kankanaey language |
E139670
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Kankanai |
E269402
|
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: Kankanai | Statement: [Kankanaey language, hasAlternativeName, Kankanai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kankanai Context triple: [Kankanaey language, hasAlternativeName, Kankanai]
-
A.
Nakanai
chosen
Nakanai is an Austronesian language spoken on the island of New Britain in Papua New Guinea, known for its role in the linguistic diversity of the Bismarck Archipelago.
-
B.
Kanai
Kanai was a former municipality in Niigata Prefecture, Japan, that later became part of the city of Sado through a merger.
-
C.
Nakawa
Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
-
D.
Kitadake
Kitadake is one of the principal peaks of the active Sakurajima volcanic complex in Kagoshima Prefecture, Japan.
-
E.
Kanda
Kanda is a historic commercial and educational district in central Tokyo known for its bookstores, universities, and traditional shrines.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0631b32308190a8211043d1caa6e6 |
completed | March 22, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c24406809c8190a827a52abce88ecc |
completed | March 24, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:23 p.m.