Triple
T331123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrobús |
E6627
|
entity |
| Predicate | country |
P26
|
FINISHED |
| Object | Mexico |
E346
|
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: Mexico | Statement: [Metrobús, country, Mexico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mexico Context triple: [Metrobús, country, Mexico]
-
A.
Mexico
chosen
Mexico is a large North American country known for its rich pre-Columbian and colonial history, diverse cultures, and influential cuisine and arts.
-
B.
State of Mexico
The State of Mexico is a populous federal entity in central Mexico that surrounds much of Mexico City and is a major political, economic, and industrial hub of the country.
-
C.
Guatemala
Guatemala is a Central American country known for its Mayan heritage, volcanic landscapes, and vibrant indigenous cultures.
-
D.
Republic of Yucatán
The Republic of Yucatán was a short-lived 19th-century independent nation in southeastern Mexico, centered on the Yucatán Peninsula, that briefly seceded from Mexico before rejoining it.
-
E.
Cuba
Cuba is a Caribbean island nation known for its communist government, historic Havana architecture, classic cars, and influential music and culture.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eaafd1a48190a6d001af3c2a5318 |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3cfec426081908a0c7e968846515a |
completed | March 1, 2026, 5:34 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.