Triple
T17163881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivas Department |
E416554
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Rivas |
E102655
|
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: Rivas | Statement: [Rivas Department, hasMunicipality, Rivas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rivas Context triple: [Rivas Department, hasMunicipality, Rivas]
-
A.
Rivas
chosen
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
B.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
C.
Varela
Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
-
D.
Valladares
Valladares is a Spanish surname historically associated with nobility and notable figures such as colonial administrators and politicians.
-
E.
Cifuentes
Cifuentes is a historic town in the province of Guadalajara, Spain, known for its medieval architecture and location within the Alcarria region.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f913c84481908bb5da8bcc6a2e62 |
completed | April 18, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fc687788190864fa3922a31184d |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:37 a.m.