Triple
T19759899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avery v. Midland County |
E474598
|
entity |
| Predicate | isRelatedField |
P6979
|
FINISHED |
| Object | election law |
—
|
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: election law | Statement: [Avery v. Midland County, isRelatedField, election law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRelatedField Context triple: [Avery v. Midland County, isRelatedField, election law]
-
A.
hasRelatedField
Indicates that one field is associated with or connected to another field in a relevant or contextually meaningful way.
-
B.
isRelatedName
Indicates that one name is connected to another through a variant, derivative, or otherwise non-identical but related naming relationship.
-
C.
relatedField
chosen
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
D.
isRelatedSymbol
Indicates that one symbol has a defined relationship or association with another symbol, such as similarity, correspondence, or functional connection.
-
E.
inSameFieldAs
Indicates that two entities work, study, or specialize within the same professional or academic field.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6531e79fc819094a9f88182e90dab |
completed | April 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.