Triple
T38574998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Türkiye Romanları |
E929376
|
entity |
| Predicate | mainlyUrban |
P191443
|
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: [Türkiye Romanları, mainlyUrban, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainlyUrban Context triple: [Türkiye Romanları, mainlyUrban, true]
-
A.
mainUrbanTerminus
Indicates the primary urban endpoint or central city location where a route, line, or service terminates.
-
B.
hasUrbanTrend
Indicates that something exhibits characteristics, patterns, or influences associated with urban environments or city-oriented lifestyles.
-
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
Indicates that an entity previously held an urban classification or status during a specified time period.
-
E.
isUrbanNeighborhood
Indicates that a given area functions as a neighborhood located within an urban or city environment.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdfbafbf48190abe38ec0003a6419 |
completed | May 7, 2026, 6:53 p.m. |
Created at: May 3, 2026, 4:32 p.m.