Triple
T2121878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pakhto |
E43942
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Wanetsi |
E46312
|
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: Wanetsi | Statement: [Pakhto, hasDialect, Wanetsi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanetsi Context triple: [Pakhto, hasDialect, Wanetsi]
-
A.
Wanetsi
chosen
Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
-
B.
Sanglechi
Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
-
C.
Tshiguvhu
Tshiguvhu is a regional dialect of the Tshivenda language spoken by Venda communities in parts of South Africa.
-
D.
Mwotlap
Mwotlap is an Oceanic Austronesian language spoken on Mota Lava and nearby islands in northern Vanuatu.
-
E.
Apswa
Apswa is the endonym used by the Abkhaz people to refer to themselves and their language.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb51e8088190a1aeafee4e8dff63 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51999ca08190a726040df6825ba5 |
completed | March 9, 2026, 4:50 a.m. |
Created at: March 4, 2026, 7:44 p.m.