Triple
T6900444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia magistrate courts |
E159480
|
entity |
| Predicate | eachCountyHas |
P74014
|
FINISHED |
| Object | at least one magistrate court |
—
|
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: at least one magistrate court | Statement: [Georgia magistrate courts, eachCountyHas, at least one magistrate court]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eachCountyHas Context triple: [Georgia magistrate courts, eachCountyHas, at least one magistrate court]
-
A.
hasNumberOfCounties
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
B.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
C.
inCounty
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
D.
hasCentralCounty
Indicates that an administrative or geographic region is associated with a specific county that serves as its central or primary county.
-
E.
hasCountyCode
Indicates that an entity is associated with a specific county identified by a standardized county code.
- 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9603f448190bb9f963c17ca206d |
completed | March 27, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:24 p.m.