Triple
T16600071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will v. Michigan Department of State Police, 491 U.S. 58 (1989) |
E403306
|
entity |
| Predicate | reporterVolume |
P123480
|
FINISHED |
| Object | 491 |
—
|
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: 491 | Statement: [Will v. Michigan Department of State Police, 491 U.S. 58 (1989), reporterVolume, 491]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reporterVolume Context triple: [Will v. Michigan Department of State Police, 491 U.S. 58 (1989), reporterVolume, 491]
-
A.
reporterNameVolumeRange
Indicates that a reporter’s name is associated with a specific range of volume numbers in which they appear or are relevant.
-
B.
volumeLevels
Indicates the relative loudness or intensity settings assigned to one or more entities or audio outputs.
-
C.
reporterNumber
Indicates the identifier or count associated with the reporter involved in a given event or relationship.
-
D.
volume
Indicates the amount of three-dimensional space an entity occupies or contains.
-
E.
reporterType
Indicates the specific role or category of reporter associated with an entity or event.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d75772c8190b02aef02ea6788e1 |
completed | April 18, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:16 a.m.