Triple
T16024816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mam language |
E388690
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object | Tacaná Mam |
E570095
|
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: Tacaná Mam | Statement: [Mam language, hasDialects, Tacaná Mam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tacaná Mam Context triple: [Mam language, hasDialects, Tacaná Mam]
-
A.
Tacaná
chosen
Tacaná is a municipality in western Guatemala, located near the Mexican border and known for its proximity to the Tacaná volcano.
-
B.
Zihuatanejo
Zihuatanejo is a coastal resort city on Mexico’s Pacific Ocean, known for its beaches, fishing, and laid-back atmosphere.
-
C.
Sierra Totonac
Sierra Totonac is a variant of the Totonac indigenous language spoken in the mountainous regions of eastern Mexico.
-
D.
Sierra de Manantlán
Sierra de Manantlán is a mountainous region in western Mexico known for its rich biodiversity and protected natural landscapes.
-
E.
Pico Mayor
Pico Mayor is the highest and most prominent summit of the Acatenango volcano in Guatemala, known for its panoramic views of the surrounding volcanic landscape.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183258c708190acf1588c7ccb254c |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf31c8d8819096c562ba1453f3c0 |
completed | May 10, 2026, 12:20 a.m. |
Created at: April 10, 2026, 4:55 a.m.