Triple
T7036128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biobío Province |
E163388
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Cabrero |
E105387
|
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: Cabrero | Statement: [Biobío Province, containsCity, Cabrero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cabrero Context triple: [Biobío Province, containsCity, Cabrero]
-
A.
Cabrero
chosen
Cabrero is a small Chilean city located in the Biobío Region, known for its agricultural activities and role as a local transport and services hub.
-
B.
O’Donojú
O’Donojú is the surname of Juan O’Donojú, the last Spanish political chief of New Spain who played a key role in Mexico’s transition to independence.
-
C.
Velasco
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
-
D.
Marín
Marín is a coastal town in the province of Pontevedra, Galicia, Spain, known for its naval traditions and as a base of the Spanish Navy.
-
E.
Dorado
Dorado is a coastal municipality in northern Puerto Rico known for its upscale resorts, golf courses, and residential communities.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e220508c8190b8950cf38280b8c2 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c775a211f88190afe5ed466abcac7a |
completed | March 28, 2026, 6:30 a.m. |
Created at: March 27, 2026, 2:36 p.m.