Triple
T1865142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billboard Most Played in Jukeboxes |
E34902
|
entity |
| Predicate | hasUnitOfFrequency |
P15625
|
FINISHED |
| Object | weekly |
—
|
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: weekly | Statement: [Billboard Most Played in Jukeboxes, hasUnitOfFrequency, weekly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnitOfFrequency Context triple: [Billboard Most Played in Jukeboxes, hasUnitOfFrequency, weekly]
-
A.
timeUnitOfFrequency
chosen
Indicates the unit of time (e.g., day, week, month) in which a given frequency is measured or expressed.
-
B.
typicalFrequencyUnit
Indicates the unit of measurement typically used to express the frequency of an event, action, or occurrence.
-
C.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
D.
hasFrequencyCategory
Indicates that something is associated with a particular classification of how often it occurs or is used.
-
E.
hasFrequencyNote
Indicates that something is associated with a specific note describing how often it occurs or is repeated.
- 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.