Triple
T12193000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Electric City |
E290509
|
entity |
| Predicate | appliedToMunicipalityType |
P90780
|
FINISHED |
| Object | 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: city | Statement: [The Electric City, appliedToMunicipalityType, city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToMunicipalityType Context triple: [The Electric City, appliedToMunicipalityType, city]
-
A.
hasMunicipalityType
Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
-
B.
affectsMunicipality
Indicates that one entity has an impact on, influences, or brings about changes in a specific municipality.
-
C.
isInMunicipality
Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
-
D.
appliesToUrbanAreaType
chosen
Indicates that something (such as a rule, measure, or classification) is applicable specifically to a particular type or category of urban area.
-
E.
isMunicipal
Indicates that something belongs to, is administered by, or is characteristic of a municipality or local city government.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:50 p.m.