Triple
T26867461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santiago Tilantongo |
E676512
|
entity |
| Predicate | hasIndigenousToponymy |
P191080
|
FINISHED |
| Object | Mixtec toponymy |
—
|
LITERAL 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: Mixtec toponymy | Statement: [Santiago Tilantongo, hasIndigenousToponymy, Mixtec toponymy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndigenousToponymy Context triple: [Santiago Tilantongo, hasIndigenousToponymy, Mixtec toponymy]
-
A.
hasEthnolinguisticOriginOfToponym
Indicates that a toponym (place name) originates from or is derived from a particular ethnolinguistic group or language.
-
B.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
C.
includesToponym
Indicates that one entity contains or references a place name (toponym) associated with another entity.
-
D.
indigenousNameOf
Indicates that one entity is the name used for another entity in an indigenous or native language.
-
E.
hasWritingSystemOfToponym
Indicates that a toponym is written or represented using a particular writing system.
- F. None of above. chosen
Provenance (4 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_69eee9ba94bc8190b44c5d4397d04ecd |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcda35dc048190a3c90e15230900e0 |
completed | May 7, 2026, 6:30 p.m. |
Created at: April 27, 2026, 5:29 a.m.