Triple
T17580011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bella Bella |
E428175
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Waglisla |
E441678
|
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: Waglisla | Statement: [Bella Bella, alternateName, Waglisla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waglisla Context triple: [Bella Bella, alternateName, Waglisla]
-
A.
Waglisla
chosen
Waglisla is the main village and cultural center of the Heiltsuk First Nation on the central coast of British Columbia, Canada.
-
B.
Glais
Glais is a village in the Swansea Valley in South Wales, known for its residential character and proximity to both Swansea and the surrounding countryside.
-
C.
Glaus
Glaus is a surname most notably associated with former Major League Baseball third baseman Troy Glaus.
-
D.
Yungay
Yungay is a small Chilean city located in the Ñuble Region, known for its agricultural surroundings and Andean foothill landscapes.
-
E.
Yungay
Yungay is a town in north-central Peru known for being devastated by a catastrophic earthquake and landslide in 1970, after which a new settlement was built nearby.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463cdb1608190a7e249ad6531b1dc |
completed | April 19, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01ddedc4808190a9652fce605741af |
completed | May 11, 2026, 1:47 p.m. |
Created at: April 10, 2026, 5:50 a.m.