Triple
T15555202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Yana |
E370848
|
entity |
| Predicate | ethnolinguisticGroup |
P3349
|
FINISHED |
| Object | Yana |
E1152381
|
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: Yana | Statement: [Southern Yana, ethnolinguisticGroup, Yana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yana Context triple: [Southern Yana, ethnolinguisticGroup, Yana]
-
A.
Yana
Yana is a professor character from the Doctor Who universe whose true identity is central to a major plot twist.
-
B.
Yana
chosen
Yana is a small family of extinct Native American languages once spoken in northern California.
-
C.
Yani
Yani is an Indonesian surname most notably associated with General Ahmad Yani, a national hero and high-ranking military officer killed during the 1965 coup attempt.
-
D.
Yua
Yua is a small genus of flowering plants in the grape family Vitaceae, native to parts of East Asia.
-
E.
Yanaoca
Yanaoca is a small Andean town in southern Peru that serves as the administrative and commercial center of Canas Province in the Cusco Region.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a97dbfc8190a98cbbac5e71ba88 |
completed | April 16, 2026, 2:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c3e67c881909a9fa1e483a364be |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:09 a.m.