Triple
T9192455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katuic branch |
E220622
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Katu language |
E216902
|
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: Katu language | Statement: [Katuic branch, hasLanguage, Katu language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katu language Context triple: [Katuic branch, hasLanguage, Katu language]
-
A.
Katu language
chosen
Katu language is an Austroasiatic language spoken by the Katu people primarily in Laos and central Vietnam.
-
B.
Kati language
The Kati language is a Nuristani language spoken primarily in parts of northeastern Afghanistan and adjacent regions of Pakistan.
-
C.
Kiga language
The Kiga language is a Bantu language spoken primarily by the Bakiga people of southwestern Uganda.
-
D.
Kawaiisu language
Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
-
E.
Kisukuma language
Kisukuma is a major Bantu language spoken primarily by the Sukuma people in northwestern Tanzania.
- 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd5c077b4819086c74e91ee4bd75e |
completed | April 1, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c2bb2c481909db8c223aececf37 |
completed | April 4, 2026, 12:32 a.m. |
Created at: March 30, 2026, 7:24 p.m.