Triple
T20027193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nueva Segovia |
E495014
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Macuelizo |
—
|
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: Macuelizo | Statement: [Nueva Segovia, hasMunicipality, Macuelizo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macuelizo Context triple: [Nueva Segovia, hasMunicipality, Macuelizo]
-
A.
Macuelizo
chosen
Macuelizo is a town and municipality in northern Nicaragua’s Nueva Segovia Department, known for its rural economy and proximity to the Honduran border.
-
B.
Maceda
Maceda is a civil parish located within the municipality of Ovar in Portugal.
-
C.
Balbuena
Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
-
D.
Guanito
Guanito is a rural municipal district within the San Juan de la Maguana municipality in the San Juan Province of the Dominican Republic.
-
E.
Pilcaniyeu
Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628e1eec81908e4c9b2b0b68f0e4 |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:35 p.m.