Triple
T35281917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankie and Johnny |
E1018955
|
entity |
| Predicate | widelyRecorded |
P22990
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Frankie and Johnny, widelyRecorded, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widelyRecorded Context triple: [Frankie and Johnny, widelyRecorded, true]
-
A.
widelyRecordedIn
Indicates that an event, fact, or phenomenon has been documented or captured in many different records, sources, or media.
-
B.
isOftenRecordedWith
Indicates that one entity is frequently documented, captured, or logged at the same time as another entity.
-
C.
isFrequentlyRecorded
chosen
Indicates that an entity is captured or documented many times within a given dataset, medium, or context.
-
D.
frequentlyRecordedBy
Indicates that an entity is often documented, captured, or logged by a particular agent, system, or recording process.
-
E.
isPopularRecordingOf
Indicates that one entity is a widely known or frequently enjoyed version or performance of another work, such as a song or composition.
- 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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78fdaeaf88190a6b24a96634ddfe1 |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2f52e08190a77661223a96c601 |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 3, 2026, 4:03 p.m.