Triple
T1355919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hialeah, Florida |
E28986
|
entity |
| Predicate | regionalCode |
P3446
|
FINISHED |
| Object | FIPS code 12-30000 |
—
|
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 12-30000 | Statement: [Hialeah, Florida, regionalCode, FIPS code 12-30000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalCode Context triple: [Hialeah, Florida, regionalCode, FIPS code 12-30000]
-
A.
regionCodeType
Indicates the classification or format type used for a given region code within a coding or identification system.
-
B.
hasRegionCode
chosen
Indicates that an entity is associated with a specific regional identifier or code.
-
C.
regionNumber
Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
-
D.
NUTSRegionCode
Indicates the classification of an entity according to the NUTS (Nomenclature of Territorial Units for Statistics) regional coding system used for statistical regions.
-
E.
hasAirportCodeRegion
Indicates that an airport code is associated with, or belongs to, a specific geographic or administrative region.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c28c8dd0819082f94c9e7c837c5f |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef7700c819099b294e8d9320e70 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.