Triple
T4234273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonia Cultura Maya |
E94654
|
entity |
| Predicate | typeOfHumanSettlement |
P11334
|
FINISHED |
| Object | colonia |
—
|
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: colonia | Statement: [Colonia Cultura Maya, typeOfHumanSettlement, colonia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHumanSettlement Context triple: [Colonia Cultura Maya, typeOfHumanSettlement, colonia]
-
A.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
B.
typeOfToponym
Indicates the specific category or kind of place name (toponym) that applies to a given geographic entity.
-
C.
humanSettlementStatus
Indicates the classification of a place in terms of its status as a human settlement (e.g., whether and how it is recognized or designated as a populated place).
-
D.
hasPopulationCenterType
chosen
Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
-
E.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
- F. None of above.
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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e6705548190b695b3789d713b4a |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f3bd188190b0cd613e8a5c1683 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.