Triple
T2898810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guanajuato International Airport |
E62605
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Silao |
E63068
|
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: Silao | Statement: [Guanajuato International Airport, locatedNear, Silao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silao Context triple: [Guanajuato International Airport, locatedNear, Silao]
-
A.
Surigaonon
Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
-
B.
Malpaso
Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
-
C.
Canlaon
Canlaon is a city in the Philippines known for its proximity to Mount Kanlaon, an active volcano and prominent natural landmark on Negros Island.
-
D.
Silao Municipality
chosen
Silao Municipality is an administrative region in the state of Guanajuato, Mexico, known for its industrial activity and proximity to the city of León and the Bajío industrial corridor.
-
E.
Los Baños
Los Baños is a municipality in the Philippines known as a major center for agricultural research and education, particularly in rice science.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0ad7bbc8190822738baa6935b74 |
completed | March 7, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0318c544881909f6aabfb2d25e724 |
completed | March 10, 2026, 2:58 p.m. |
Created at: March 6, 2026, 10:10 p.m.