Triple
T34974146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reefer Head Woman |
E1008622
|
entity |
| Predicate | isMostFamouslyRecordedBy |
P56625
|
FINISHED |
| Object | Aerosmith |
—
|
NE NERFINISHED |
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: Aerosmith | Statement: [Reefer Head Woman, isMostFamouslyRecordedBy, Aerosmith]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostFamouslyRecordedBy Context triple: [Reefer Head Woman, isMostFamouslyRecordedBy, Aerosmith]
-
A.
mostFamouslyRecordedBy
chosen
Indicates that an item (such as a work, song, or performance) is best known or most widely associated with having been recorded by a particular entity.
-
B.
madeInternationallyFamousBy
Indicates that one entity became widely known across multiple countries as a result of the actions, influence, or association of another entity.
-
C.
famousRecord
Indicates that a particular record (such as a song, album, or performance) is widely known and recognized as notable or distinguished.
-
D.
isPopularRecordingOf
Indicates that one entity is a widely known or frequently enjoyed version or performance of another work, such as a song or composition.
-
E.
widelyRecordedIn
Indicates that an event, fact, or phenomenon has been documented or captured in many different records, sources, or media.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.