Triple
T28197056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Too Much Love Will Kill You |
E716474
|
entity |
| Predicate | queenVersionFeatures |
P27793
|
FINISHED |
| Object | Freddie Mercury lead vocals |
—
|
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: Freddie Mercury lead vocals | Statement: [Too Much Love Will Kill You, queenVersionFeatures, Freddie Mercury lead vocals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queenVersionFeatures Context triple: [Too Much Love Will Kill You, queenVersionFeatures, Freddie Mercury lead vocals]
-
A.
featureOfReleases
Indicates that certain features are associated with, included in, or introduced as part of specific releases.
-
B.
featuresPrincess
Indicates that something includes or prominently presents a princess as a central element or character.
-
C.
featuresReimaginedVersionOf
chosen
Indicates that something includes or presents a newly interpreted or updated version of another existing work or element.
-
D.
chiefQueen
Indicates that one entity is the primary or highest-ranking queen in relation to another entity.
-
E.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:28 p.m.