Triple
T6269584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Telephone Man |
E140494
|
entity |
| Predicate | vocalGroupSize |
P20922
|
FINISHED |
| Object | five-member boy band |
—
|
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: five-member boy band | Statement: [Mr. Telephone Man, vocalGroupSize, five-member boy band]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocalGroupSize Context triple: [Mr. Telephone Man, vocalGroupSize, five-member boy band]
-
A.
typicalNumberOfVoices
Indicates the usual or characteristic number of distinct voices or parts involved in performing or realizing something (such as a musical work or texture).
-
B.
hasApproximateNumberOfMusicians
chosen
Indicates that an entity is associated with an estimated or approximate count of musicians involved with it.
-
C.
vocalForces
Indicates a relationship where one entity uses vocal expression (such as speech, singing, or sound) to exert influence, pressure, or compulsion on another entity.
-
D.
hasFemaleVocalist
Indicates that the subject entity features or includes at least one female vocalist as a performer.
-
E.
vocalRange
Indicates the span of pitches or notes that an entity (such as a singer or instrument) is capable of producing.
- 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_69c008cabc4081909723e2547c9d6cc0 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063a3f1d081908ccff88db94b1f9c |
completed | March 22, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69c05606fb50819082d1a5a91e5030b6 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:25 p.m.