Triple
T1865128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billboard Most Played in Jukeboxes |
E34902
|
entity |
| Predicate | temporalClassification |
P18401
|
FINISHED |
| Object | historical chart |
—
|
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: historical chart | Statement: [Billboard Most Played in Jukeboxes, temporalClassification, historical chart]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalClassification Context triple: [Billboard Most Played in Jukeboxes, temporalClassification, historical chart]
-
A.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
B.
classificationStart
Indicates the point in time or process at which a classification or categorization of an entity begins.
-
C.
temporalRelation
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
D.
chronologicallyClassifiedAs
chosen
Indicates that something is assigned to or placed within a specific time period or chronological category.
-
E.
previousClassification
Indicates that one classification precedes another in time or in an ordered sequence of classifications.
- 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe02c3c819093a4744b476106ca |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.