Triple
T258739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago metropolitan area |
E5493
|
entity |
| Predicate | statisticalAreaType |
P6822
|
FINISHED |
| Object | Combined Statistical Area |
—
|
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: Combined Statistical Area | Statement: [Chicago metropolitan area, statisticalAreaType, Combined Statistical Area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statisticalAreaType Context triple: [Chicago metropolitan area, statisticalAreaType, Combined Statistical Area]
-
A.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
B.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
C.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
electoralDistrictType
Indicates the specific category or kind of electoral district associated with an entity (e.g., federal, state, local).
-
E.
censusRegion
Indicates the broader census-defined geographic region in which an entity (such as a place or population unit) is located or classified.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25f921c2881908821ca2c03815eae |
completed | Feb. 28, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69a25b6b3ea88190bbd858999e42efae |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.