Triple
T8219725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fog City |
E192026
|
entity |
| Predicate | associatedUrbanForm |
P749
|
FINISHED |
| Object | high-density development |
—
|
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: high-density development | Statement: [Fog City, associatedUrbanForm, high-density development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedUrbanForm Context triple: [Fog City, associatedUrbanForm, high-density development]
-
A.
isUrbanForm
Indicates that an entity represents or exhibits characteristics of an urban built environment or city-like spatial structure.
-
B.
formsUrbanAreaWith
Indicates that two or more settlements are geographically and functionally connected so that together they constitute a single continuous urban area.
-
C.
locatedInUrbanizationType
Indicates that one entity is situated within, or belongs to, a specific type or category of urbanized area (e.g., city, suburb, metropolitan zone).
-
D.
urbanAreaType
chosen
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
E.
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.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7772b76c8190b1952650c736eb91 |
completed | March 31, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.