Triple
T12757118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fugue in D major, BWV 850 |
E304887
|
entity |
| Predicate | usesSequentialPassages |
P106742
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fugue in D major, BWV 850, usesSequentialPassages, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSequentialPassages Context triple: [Fugue in D major, BWV 850, usesSequentialPassages, yes]
-
A.
narrativeSequence
Indicates that one event or narrative element follows another in a temporal or logical storytelling order.
-
B.
parallelPassage
Indicates that one text segment corresponds closely in content or structure to another, such that they can be considered parallel versions or accounts of the same material.
-
C.
continuedThrough
Indicates that an event, state, or process persisted without interruption across or beyond a specified point, period, or boundary.
-
D.
numberOfPassages
Indicates the total count of distinct passages associated with or contained within a given entity or context.
-
E.
followsSectionOf
Indicates that one section directly comes after or succeeds another section in an ordered structure.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8b57b88190b29b8fdca415c81c |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:27 p.m.