Triple
T8354572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodfarm Township, Grundy County, Illinois |
E196651
|
entity |
| Predicate | usesStateCode |
P80674
|
FINISHED |
| Object | IL |
—
|
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: IL | Statement: [Goodfarm Township, Grundy County, Illinois, usesStateCode, IL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesStateCode Context triple: [Goodfarm Township, Grundy County, Illinois, usesStateCode, IL]
-
A.
isInUSState
Indicates that one entity (typically a place or location) is geographically located within the boundaries of a specific U.S. state.
-
B.
stateOrTerritory
Indicates that one entity is a state or territory that is politically or administratively associated with another entity.
-
C.
usedByStateOrTerritory
Indicates that something (such as an object, system, or resource) is utilized or employed by a specific state or territory.
-
D.
respondentState
Indicates the state or jurisdiction in which the respondent is located, resides, or is legally associated.
-
E.
associatedWithStateCode
chosen
Indicates that an entity has a connection or linkage to a particular state identified by its state code.
- 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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8048edb88190a1980ad74818b898 |
completed | March 31, 2026, 8:05 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.