Triple
T8544081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | And You and I |
E202276
|
entity |
| Predicate | usesVocalHarmony |
P70922
|
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: [And You and I, usesVocalHarmony, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVocalHarmony Context triple: [And You and I, usesVocalHarmony, yes]
-
A.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
B.
vocalHarmonyType
chosen
Indicates the specific kind or style of vocal harmony relationship that exists between the involved vocal parts or voices.
-
C.
hasVocalForces
Indicates that an entity involves or employs vocal performers or vocal parts as a contributing force.
-
D.
hasNotableVocalType
Indicates that an entity is associated with a specific, noteworthy type or quality of vocalization or voice.
-
E.
hasVocalStyleComparedTo
Indicates a comparison between entities based on the similarity or resemblance of their vocal style.
- 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_69ca832461e88190a654c5e44e233aa8 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe6e381d4819084e230389a3ecb77 |
completed | March 31, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:18 p.m.