Triple
T7710426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiwa people |
E174735
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Tiwa |
E681141
|
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: Tiwa | Statement: [Tiwa people, nativeName, Tiwa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiwa Context triple: [Tiwa people, nativeName, Tiwa]
-
A.
Tiwa
Tiwa is a Tanoan language spoken by several Pueblo communities in northern New Mexico and southern Colorado, central to their cultural and ceremonial life.
-
B.
Tiwa
chosen
The Tiwa are an indigenous ethnic community of Northeast India known for their distinct language, vibrant festivals, and traditional agrarian lifestyle.
-
C.
Siwi
Siwi is a Berber language spoken primarily in Egypt’s Siwa Oasis, known for its unique features and relative isolation from other Berber varieties.
-
D.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
E.
Wito
Wito is a personal name used as an alternative spelling of Wido, typically found in certain European linguistic and cultural contexts.
- 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_69c6995b3e8c8190833108f883d5f53c |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ad6b788190892b96ab523d111f |
completed | March 27, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b505c7f88190ac058c1a27d758ca |
completed | March 29, 2026, 5:13 a.m. |
Created at: March 27, 2026, 4:04 p.m.