Triple
T1335874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City Hall, London |
E28746
|
entity |
| Predicate | energyEfficiencyFeature |
P27882
|
FINISHED |
| Object | double-skin façade |
—
|
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: double-skin façade | Statement: [City Hall, London, energyEfficiencyFeature, double-skin façade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyEfficiencyFeature Context triple: [City Hall, London, energyEfficiencyFeature, double-skin façade]
-
A.
energyUse
Indicates the amount or rate at which an entity consumes energy to perform its functions or activities.
-
B.
designEnergy
Indicates that an entity is responsible for planning, specifying, or determining the energy-related characteristics or performance of another entity.
-
C.
hasEnergyManagement
Indicates that an entity possesses or is associated with a system, capability, or function for monitoring, controlling, or optimizing energy use.
-
D.
energyType
Indicates the kind or category of energy associated with an entity or process.
-
E.
fuelEfficiency
Indicates how effectively an entity uses fuel to perform a given amount of work or travel a certain distance.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c1bf31988190a659f48fe018f4bc |
completed | March 1, 2026, 10:46 p.m. |
Created at: March 1, 2026, 7:55 p.m.