Triple
T24798783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myeon |
E620462
|
entity |
| Predicate | levelComparedToCounty |
P157310
|
FINISHED |
| Object | below county |
—
|
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: below county | Statement: [Myeon, levelComparedToCounty, below county]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levelComparedToCounty Context triple: [Myeon, levelComparedToCounty, below county]
-
A.
interCountyLevel
Indicates that the relationship or action occurs between or spans across multiple counties or county-level jurisdictions.
-
B.
countyEquivalent
Indicates that two territorial or administrative units are considered equivalent in status or function to a county within a given governmental or geographic framework.
-
C.
isInCountySeatAreaOfInfluence
Indicates that one location lies within the geographic or functional area of influence of a county seat.
-
D.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
E.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f42b11251881908070b93355de64ad |
completed | May 1, 2026, 4:24 a.m. |
Created at: April 18, 2026, 4:49 a.m.