Triple
T1539048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County of Allegheny v. ACLU |
E32821
|
entity |
| Predicate | legalTestApplied |
P17991
|
FINISHED |
| Object | endorsement test |
—
|
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: endorsement test | Statement: [County of Allegheny v. ACLU, legalTestApplied, endorsement test]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalTestApplied Context triple: [County of Allegheny v. ACLU, legalTestApplied, endorsement test]
-
A.
appliedTest
chosen
Indicates that a test has been administered or carried out on a particular subject or object.
-
B.
legalOutcome
Indicates the resulting legal status, decision, or consequence that follows from a legal process, action, or judgment.
-
C.
legalCase
Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
-
D.
legalProcedureUsed
Indicates that a particular legal procedure or process is applied or employed in relation to a case, action, or legal matter.
-
E.
legalDoctrineChallenged
Indicates that a particular legal doctrine is being disputed, questioned, or contested, typically through litigation or formal legal argument.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.