Triple
T16955875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruta 1 |
E411299
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object | San José |
E29798
|
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 José | Statement: [Ruta 1, hasTerminus, San José]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San José Context triple: [Ruta 1, hasTerminus, San José]
-
A.
San José
chosen
San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
-
B.
San José
San José is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing rural landscape in the Andean region.
-
C.
San José
San José is a station on the Buenos Aires Underground, part of the city’s rapid transit network in Argentina.
-
D.
San José
San José is a professional football club from Oruro, Bolivia, known for competing in the country's top-tier league and having a passionate local fan base.
-
E.
San José
San José is a major city in Northern California’s Silicon Valley, known as a hub for technology, innovation, and diverse 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_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_6a00dc06e6b481908d8032f5772762c9 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:31 a.m.