Triple
T12871178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masdar |
E307851
|
entity |
| Predicate | MasdarCityConcept |
P70554
|
FINISHED |
| Object | low-carbon city |
—
|
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: low-carbon city | Statement: [Masdar, MasdarCityConcept, low-carbon city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MasdarCityConcept Context triple: [Masdar, MasdarCityConcept, low-carbon city]
-
A.
smartCityProjects
Indicates a relationship where a city undertakes or is associated with projects that apply digital, data-driven, or intelligent technologies to improve urban services and infrastructure.
-
B.
modernCityBuiltAround
Indicates that a contemporary or recently developed city has been constructed encircling or surrounding a particular central feature, structure, or area.
-
C.
isScienceCity
Indicates that a city is recognized or designated as a center for scientific research, education, or technological innovation.
-
D.
urbanDesignGoal
chosen
Indicates a goal or intended outcome related to the planning, shaping, or improvement of urban spaces and environments.
-
E.
urbanDesigner
Indicates a relationship where an entity practices or is responsible for planning and designing urban spaces, environments, or city layouts.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:38 p.m.