Triple
T3266182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiapas |
E68532
|
entity |
| Predicate | containsArchaeologicalSite |
P11933
|
FINISHED |
| Object | Toniná |
E270166
|
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: Toniná | Statement: [Chiapas, containsArchaeologicalSite, Toniná]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toniná Context triple: [Chiapas, containsArchaeologicalSite, Toniná]
-
A.
Toniná
chosen
Toniná is an ancient Maya archaeological site in Chiapas, Mexico, known for its towering acropolis, intricate stone carvings, and evidence of powerful Classic-period warfare and politics.
-
B.
Tonalá
Tonalá is a municipality and city in the Guadalajara metropolitan area of Jalisco, Mexico, known for its traditional pottery and handicrafts.
-
C.
Matlatzinca
Matlatzinca is an indigenous language of central Mexico spoken by the Matlatzinca people, primarily in the State of Mexico.
-
D.
Jalapa
Jalapa is the capital city of the Mexican state of Veracruz, known for its cool, misty climate, cultural institutions, and surrounding coffee-growing region.
-
E.
Cobá
Cobá is an ancient Maya city in Mexico’s Yucatán Peninsula, known for its extensive network of sacbeob (raised stone roads) and towering pyramid structures amid dense jungle.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcc99908190897230b4b71e2ea8 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28eed68c08190994376bfbfeae949 |
completed | March 12, 2026, 10:01 a.m. |
Created at: March 8, 2026, 3:09 p.m.