Triple
T3041347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doon, Iowa |
E83135
|
entity |
| Predicate | isInFIPSCounty |
P227
|
FINISHED |
| Object | 119 |
—
|
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: 119 | Statement: [Doon, Iowa, isInFIPSCounty, 119]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInFIPSCounty Context triple: [Doon, Iowa, isInFIPSCounty, 119]
-
A.
FIPSCode
chosen
Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
-
B.
isInCountySubdivision
Indicates that one entity (typically a place or address) is located within the boundaries of a specific county subdivision.
-
C.
isInUnitedStatesMunicipalHierarchy
Indicates that one administrative or governmental unit occupies a specific level or position within the municipal hierarchy of the United States (e.g., city, town, county, or similar local jurisdiction).
-
D.
isInUSState
Indicates that one entity (typically a place or location) is geographically located within the boundaries of a specific U.S. state.
-
E.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b5b92088190971bed04e65c5917 |
completed | March 8, 2026, 3:52 p.m. |
| PD | Predicate disambiguation | batch_69ad961fc62c819087c4c3a44b00847d |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.