Triple
T1220078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake County, Indiana |
E26198
|
entity |
| Predicate | hasMetropolitanRole |
P5047
|
FINISHED |
| Object | suburban area of Chicago |
—
|
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: suburban area of Chicago | Statement: [Lake County, Indiana, hasMetropolitanRole, suburban area of Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetropolitanRole Context triple: [Lake County, Indiana, hasMetropolitanRole, suburban area of Chicago]
-
A.
hasMetropolitan
chosen
Indicates that an entity is associated with, served by, or located within a specific metropolitan area.
-
B.
hasCityRole
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
C.
hasUrbanRole
Indicates that an entity plays a specific functional or social role within an urban or city context.
-
D.
hasMetropolitanSee
Indicates that one ecclesiastical jurisdiction serves as the metropolitan (primary or overseeing) see in relation to another church territory.
-
E.
hasMetropolitanCounty
Indicates that an entity is associated with, located within, or administered by a specific metropolitan county.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be1ead088190bf44dc6ab1edf18b |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.