Triple
T23537065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agreste region of Alagoas |
E577626
|
entity |
| Predicate | hasUrbanCenterType |
P11334
|
FINISHED |
| Object | medium-sized inland towns |
—
|
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: medium-sized inland towns | Statement: [Agreste region of Alagoas, hasUrbanCenterType, medium-sized inland towns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanCenterType Context triple: [Agreste region of Alagoas, hasUrbanCenterType, medium-sized inland towns]
-
A.
isUrbanCenter
Indicates that a place functions as a primary, densely developed hub of population, services, and activities within a region.
-
B.
isUrbanCentreFor
Indicates that one place functions as the primary urban hub or central city serving another area or population.
-
C.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
-
D.
hasPopulationCenterType
chosen
Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
-
E.
containsUrbanArea
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1831688190ac06b84729bce160 |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:10 p.m.