Triple
T770609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa Zoni |
E16271
|
entity |
| Predicate | hasUrbanization |
P9969
|
FINISHED |
| Object | minimal |
—
|
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: minimal | Statement: [Playa Zoni, hasUrbanization, minimal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanization Context triple: [Playa Zoni, hasUrbanization, minimal]
-
A.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
B.
urbanizationLevel
chosen
Indicates the degree to which an area or population is characterized by urban development, infrastructure, and density of human settlement.
-
C.
hasUrbanFunction
Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
-
D.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a704fb148190b203a5bdd77e961c |
completed | March 1, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69a4a508c42c8190850a0ac7844a3ea9 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.