Triple
T37222099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Say, Brothers, Will You Meet Us |
E922910
|
entity |
| Predicate | hasTuneRelation |
P149801
|
FINISHED |
| Object | John Brown's Body |
—
|
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: John Brown's Body | Statement: [Say, Brothers, Will You Meet Us, hasTuneRelation, John Brown's Body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTuneRelation Context triple: [Say, Brothers, Will You Meet Us, hasTuneRelation, John Brown's Body]
-
A.
hasTuneOrigin
Indicates that one entity’s tune or melody originates from, is derived from, or is based on another entity.
-
B.
usesTuneOf
chosen
Indicates that one work is created to be performed with, or is based on, the melody or musical setting originally belonging to another work.
-
C.
tunedOrUntuned
Indicates whether something is in a properly adjusted or calibrated state (tuned) or not (untuned).
-
D.
isTunedTo
Indicates that one entity has been adjusted or configured to operate at, receive, or correspond to the frequency, channel, or setting of another entity.
-
E.
hasMusicalSettingsBy
Indicates that a work has been set to music or musically arranged by a specified creator or composer.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.