Triple
T7171937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mambae language |
E167219
|
entity |
| Predicate | neighboringLanguages |
P16383
|
FINISHED |
| Object | Kemak language |
E231077
|
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: Kemak language | Statement: [Mambae language, neighboringLanguages, Kemak language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kemak language Context triple: [Mambae language, neighboringLanguages, Kemak language]
-
A.
Kemak language
chosen
The Kemak language is an Austronesian language spoken primarily in the border regions of East Timor and Indonesian West Timor by the Kemak ethnic group.
-
B.
Makah language
The Makah language is a critically endangered Southern Wakashan language traditionally spoken by the Makah people of the northwestern Olympic Peninsula in Washington State, USA.
-
C.
Kendem language
The Kendem language is a Bantoid language of the Mamfe group spoken by a small community in southwestern Cameroon.
-
D.
Makurap language
The Makurap language is an indigenous Tupian language spoken by the Makurap people of the Amazon region in Brazil.
-
E.
Kitanemuk language
The Kitanemuk language is an extinct Uto-Aztecan language once spoken by the Kitanemuk people of Southern California.
- 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_69c68889a2748190a316c5e65360361a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e88b0a448190a19bd2d9e2a310a4 |
completed | March 27, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b918a838819088bd24d462101902 |
completed | March 28, 2026, 11:18 a.m. |
Created at: March 27, 2026, 2:48 p.m.