Triple
T27923208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellwood, Virginia |
E706260
|
entity |
| Predicate | federalEntityCodeType |
P58137
|
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: [Bellwood, Virginia, federalEntityCodeType, FIPS code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: federalEntityCodeType Context triple: [Bellwood, Virginia, federalEntityCodeType, FIPS code]
-
A.
federalEntityNumber
Indicates that an entity is associated with a specific identifying number assigned by a federal authority or system.
-
B.
federalGovernmentCode
chosen
Indicates that an entity is associated with, identified by, or governed under a specific code or classification defined by the federal government.
-
C.
federalGovernmentEntity
Indicates that the subject is an organization or body that forms part of a national-level (federal) government structure.
-
D.
federalEntityInvolved
Indicates that a federal-level government body or authority is involved in, associated with, or has jurisdiction over the referenced action or relationship.
-
E.
federalDistrictType
Indicates the specific category or classification of a federal district within a governmental or administrative 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_69ef96b6cc808190aab19fb18b235f4b |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 6:58 p.m.