Triple
T1231667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storey County |
E26455
|
entity |
| Predicate | countyFIPSCode |
P227
|
FINISHED |
| Object | 029 |
—
|
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: 029 | Statement: [Storey County, countyFIPSCode, 029]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyFIPSCode Context triple: [Storey County, countyFIPSCode, 029]
-
A.
FIPSCode
chosen
Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
-
B.
hasCountyCode
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
C.
federalDistrictNumber
Indicates the specific numbered federal electoral or administrative district associated with an entity.
-
D.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
E.
countyName
Indicates the specific name assigned to a county in which an entity is located or with which it is associated.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5a25348190a0665b6324c4d8f5 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.