Triple
T6170615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citizens to Preserve Overton Park v. Volpe |
E137684
|
entity |
| Predicate | hasLegalArea |
P2167
|
FINISHED |
| Object | administrative 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: administrative law | Statement: [Citizens to Preserve Overton Park v. Volpe, hasLegalArea, administrative law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalArea Context triple: [Citizens to Preserve Overton Park v. Volpe, hasLegalArea, administrative law]
-
A.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
hasCivilArea
Indicates that an administrative or political entity encompasses or is associated with a specific civil (local administrative) area.
-
C.
legalArea
chosen
Indicates the specific field or branch of law that a legal matter, case, or document pertains to.
-
D.
hasLegalRight
Indicates that an entity possesses an officially recognized legal entitlement or permission to perform an action or hold a claim regarding another entity.
-
E.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
- 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_69c008a68c508190a8d78245c865960e |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d8f97708190bebbc49c4a56c8a5 |
completed | March 22, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69c055f7f12881908e21c04e9b752ba4 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:18 p.m.