Triple
T997993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cancún |
E21538
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Quintana Roo |
E71749
|
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: Quintana Roo | Statement: [Cancún, locatedIn, Quintana Roo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quintana Roo Context triple: [Cancún, locatedIn, Quintana Roo]
-
A.
Quintana Roo
chosen
Quintana Roo is a Mexican state on the Caribbean coast known for major tourist destinations such as Cancún, Playa del Carmen, and Tulum.
-
B.
Campeche
Campeche is a historic coastal city in southeastern Mexico known for its well-preserved colonial fortifications and colorful architecture on the Gulf of Mexico.
-
C.
Yucatán Peninsula
The Yucatán Peninsula is a large landmass in southeastern Mexico extending into the Caribbean, known for its Maya archaeological sites, cenotes, and tropical coastal ecosystems.
-
D.
Chiapas
Chiapas is a southern Mexican state known for its rich indigenous cultures, Mayan archaeological sites like Palenque, and diverse natural landscapes including jungles and highlands.
-
E.
Nayarit
Nayarit is a small Pacific-coast state in western Mexico known for its beaches, coastal resorts, and diverse mountainous and tropical landscapes.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4e2ad9c81908a0f488d3f261fc3 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a18db488190bf7d604fe6a33b9e |
completed | March 7, 2026, 1:37 p.m. |
Created at: March 1, 2026, 7:41 p.m.