Triple
T16955901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruta 1 |
E411299
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | San Ramón |
E1050368
|
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: San Ramón | Statement: [Ruta 1, passesThrough, San Ramón]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Ramón Context triple: [Ruta 1, passesThrough, San Ramón]
-
A.
San Ramón
San Ramón is a locality within the municipality of Huixquilucan in the State of Mexico, forming part of the greater Mexico City metropolitan area.
-
B.
San Ramón
San Ramón is a small Nicaraguan town on Ometepe Island, known as a gateway for hiking and exploring the nearby Maderas Volcano and its surrounding natural attractions.
-
C.
San Ramón
San Ramón is a commune in the Santiago Metropolitan Region of Chile, known primarily as a residential area within Greater Santiago.
-
D.
San Ramón
San Ramón is a city that serves as the administrative and economic center of its surrounding region.
-
E.
San Ramón
chosen
San Ramón is a mid-sized city in Costa Rica’s Alajuela province known as a regional commercial and cultural hub in the country’s central highlands.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d01bb700819082a441c124be3cb6 |
completed | April 18, 2026, 6:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d4666f14819095fc3bcf5e459b61 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.