Triple
T19525732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washoe language |
E488512
|
entity |
| Predicate | hasAlternateName |
P39
|
FINISHED |
| Object | Washo |
—
|
NE NERFINISHED |
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: Washo | Statement: [Washoe language, hasAlternateName, Washo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Washo Context triple: [Washoe language, hasAlternateName, Washo]
-
A.
Washo
chosen
Washo is a Native American language isolate traditionally spoken by the Washoe people of the Lake Tahoe region in California and Nevada.
-
B.
Waase
Waase is a small village on the island of Ummanz in the German state of Mecklenburg-Vorpommern.
-
C.
Wadai
Wadai is a historical region in eastern Chad and western Sudan known for its diverse ethnic groups and use of Taman and other Saharan languages.
-
D.
Wounaan
The Wounaan are an Indigenous people of Panama and Colombia known for their rich rainforest-based culture, intricate basketry, and traditional practices closely tied to riverine environments.
-
E.
Waru
Waru is a district in Sidoarjo Regency, East Java, Indonesia, forming part of the greater Surabaya metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6363aeb8c8190be2bdd73e421af96 |
completed | April 20, 2026, 2:20 p.m. |
Created at: April 10, 2026, 1:41 p.m.