Triple
T32663286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midway, Butler County, Alabama |
E835081
|
entity |
| Predicate | usesCountry |
P193319
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Midway, Butler County, Alabama, usesCountry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCountry Context triple: [Midway, Butler County, Alabama, usesCountry, United States]
-
A.
useCountry
Indicates that one entity utilizes or operates within the jurisdiction, systems, or context of a specified country.
-
B.
usedForCountry
Indicates that something is used for, or serves a purpose related to, a specific country.
-
C.
hasCountry
Indicates that one entity possesses, is associated with, or is located within a specific country.
-
D.
usedWithCountryName
Indicates that something (such as a term, label, or identifier) is used specifically in conjunction with a country name.
-
E.
includesCountriesWith
Indicates that something contains or encompasses one or more specified countries as part of its scope or composition.
- F. None of above. chosen
Provenance (4 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_69f349303ccc8190a70d0f6e8a21d3fb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: May 1, 2026, 1:08 a.m.