Triple
T2246506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lay All Your Love on Me |
E49515
|
entity |
| Predicate | hasNotableUsage |
P5773
|
FINISHED |
| Object | featured in club and dance remixes |
—
|
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: featured in club and dance remixes | Statement: [Lay All Your Love on Me, hasNotableUsage, featured in club and dance remixes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableUsage Context triple: [Lay All Your Love on Me, hasNotableUsage, featured in club and dance remixes]
-
A.
hasUsageNote
Indicates that there is an associated explanatory note describing how or when something should be used.
-
B.
notableUse
chosen
Indicates that something is prominently or famously used by a particular entity, context, or for a specific purpose.
-
C.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
D.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
E.
hasNotableWord
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ec46b08190ae12de8b255eb71d |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.