Triple
T16512467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montt |
E401092
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | de Montt |
E401092
|
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: de Montt | Statement: [Montt, hasVariantSpelling, de Montt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de Montt Context triple: [Montt, hasVariantSpelling, de Montt]
-
A.
Balmaceda
Balmaceda is a Spanish-language surname of Chilean origin, notably borne by actor Pedro Pascal (born José Pedro Balmaceda Pascal).
-
B.
Villazón
Villazón is a Bolivian border town in the Potosí Department, known as a key commercial and transit point between Bolivia and Argentina.
-
C.
Montt
chosen
Montt is a Chilean surname most notably associated with Manuel Montt, a 19th-century president of Chile.
-
D.
Oteiza
Oteiza is a Basque surname most notably associated with the Spanish sculptor and artist Jorge Oteiza.
-
E.
Domeyko
Domeyko is a Polish-Lithuanian surname most notably borne by Ignacy Domeyko, a 19th-century geologist and national figure in Chilean science and education.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e77d9b081909235cb5ba77d1e29 |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067a31c8881909b05c49c8006785d |
completed | May 10, 2026, 11:10 a.m. |
Created at: April 10, 2026, 5:14 a.m.