Triple
T15571271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartford, New York |
E374246
|
entity |
| Predicate | hasRegionCodeSystem |
P45385
|
FINISHED |
| Object | FIPS code |
—
|
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: FIPS code | Statement: [Hartford, New York, hasRegionCodeSystem, FIPS code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionCodeSystem Context triple: [Hartford, New York, hasRegionCodeSystem, FIPS code]
-
A.
hasRegionCode
Indicates that an entity is associated with a specific regional identifier or code.
-
B.
regionCodeSystem
chosen
Indicates that a region is identified or classified according to a particular coding system for geographic or administrative areas.
-
C.
hasAreaCodeSystem
Indicates that a telephone numbering plan, region, or communication system uses or is associated with a particular area code system.
-
D.
ISO3166-2RegionCode
Indicates the standardized ISO 3166-2 code that specifies the particular primary administrative subdivision (such as a state, province, or region) to which an entity belongs.
-
E.
regionCodeType
Indicates the classification or format type used for a given region code within a coding or identification system.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e1de0488190b3639fc25f79d343 |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.