Triple
T24460848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Wouldn't Treat a Dog (The Way You Treated Me) |
E616817
|
entity |
| Predicate | hasVocalCharacter |
P156193
|
FINISHED |
| Object | emotional delivery |
—
|
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: emotional delivery | Statement: [I Wouldn't Treat a Dog (The Way You Treated Me), hasVocalCharacter, emotional delivery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVocalCharacter Context triple: [I Wouldn't Treat a Dog (The Way You Treated Me), hasVocalCharacter, emotional delivery]
-
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.
hasVocalPerspective
Indicates that one entity expresses or frames content from the point of view or voice of another entity.
-
C.
hasVocalForces
Indicates that an entity involves or employs vocal performers or vocal parts as a contributing force.
-
D.
hasVow
Indicates that one entity has made or is bound by a formal vow or promise in relation to another entity or context.
-
E.
hasVoiceIn
Indicates that an entity participates by providing a voice role or vocal performance in another entity, such as a work, production, or recording.
- 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_69e2d7ef9fe08190a0613908758b4e86 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f298ca59088190a657c863713a9eb0 |
completed | April 29, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:19 a.m.