Triple
T31730078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sala Colonia |
E809836
|
entity |
| Predicate | wasUrbanized |
P99931
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sala Colonia, wasUrbanized, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasUrbanized Context triple: [Sala Colonia, wasUrbanized, true]
-
A.
wasUrbanizedUnder
Indicates that an area became urbanized or developed into an urban environment during the rule, administration, or period associated with a specified authority or entity.
-
B.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
C.
isUrbanizing
Indicates a process in which an area or population becomes more urban in character, typically through increased development, infrastructure, and concentration of people and activities.
-
D.
wasUrbanStatus
chosen
Indicates that an entity previously held an urban classification or status during a specified time period.
-
E.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ab1e7c6c81909b9bea0662fd4f57 |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:21 p.m.