Triple
T6777334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warekena language |
E155590
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Warekana |
E618339
|
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: Warekana | Statement: [Warekena language, hasAlternativeName, Warekana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warekana Context triple: [Warekena language, hasAlternativeName, Warekana]
-
A.
Warekena
chosen
The Warekena are an Indigenous people of the Amazon region, primarily living along rivers in Brazil and Venezuela, known for their distinct Arawakan language and traditional riverine lifestyle.
-
B.
Wako
Wako is a suburban city in Saitama Prefecture, Japan, located on the northern outskirts of Tokyo and known as a residential and commuter hub.
-
C.
Varekai
Varekai is a Cirque du Soleil touring circus production known for its fantastical forest setting, acrobatic performances, and imaginative storytelling.
-
D.
Wajin
Wajin is a historical term used in East Asia to refer to the ethnic Japanese people, particularly those of the Yamato cultural and political core.
-
E.
Kibushi
Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d26725208190b64935cfd08b2aff |
completed | March 27, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723c9b1cc81908f38f203acb86002 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 2:13 p.m.