Triple
T34280742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murray v. The Charming Betsy |
E879582
|
entity |
| Predicate | hasReporterVolume |
P165340
|
FINISHED |
| Object | 6 U.S. |
—
|
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: 6 U.S. | Statement: [Murray v. The Charming Betsy, hasReporterVolume, 6 U.S.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReporterVolume Context triple: [Murray v. The Charming Betsy, hasReporterVolume, 6 U.S.]
-
A.
reporterVolume
Indicates the amount or intensity of content produced or reported by a reporter within a given context or period.
-
B.
reporterNameVolumeRange
Indicates that a reporter’s name is associated with a specific range of volume numbers in which they appear or are relevant.
-
C.
hasVolumeElement
chosen
Indicates that something includes or is associated with a specific volumetric component or element within its structure or representation.
-
D.
supportsVolumeControl
Indicates that one entity provides the capability to adjust or manage the audio volume level of another entity.
-
E.
hasVolumeRanking
Indicates that an entity is assigned a position in an ordered list based on its volume relative to others.
- 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_69f349b5f6648190b9420d94a4cd16e0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:57 a.m.