Triple
T28769577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muller v. Oregon |
E726372
|
entity |
| Predicate | hasBrief |
P173725
|
FINISHED |
| Object | Brandeis Brief |
—
|
NE NERFINISHED |
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: Brandeis Brief | Statement: [Muller v. Oregon, hasBrief, Brandeis Brief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrief Context triple: [Muller v. Oregon, hasBrief, Brandeis Brief]
-
A.
hasShort
Indicates that an entity possesses or is characterized by something of short length or duration.
-
B.
usesBreves
Indicates that one entity employs or incorporates breve diacritic marks in relation to another entity, such as in writing, notation, or transcription.
-
C.
hasBroad
Indicates that one entity possesses or exhibits a wide or extensive scope, range, or coverage in relation to another entity or context.
-
D.
usedBriefly
Indicates that an entity made short-term or momentary use of another entity or resource.
-
E.
abridgedIn
Indicates that one entity is a shortened or condensed version of the content found within another entity.
- 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_69f03198be14819098fa74e48b3749bf |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6b9a84ff88190ab5a71f7ef1e0dac |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b8fe147881908ba17483c7b13f05 |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 28, 2026, 6:15 a.m.