Triple
T33575565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Hawaii |
E860020
|
entity |
| Predicate | hasMusicalBasisIn |
P94602
|
FINISHED |
| Object | Why Did It Have to Be Me? |
—
|
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: Why Did It Have to Be Me? | Statement: [Happy Hawaii, hasMusicalBasisIn, Why Did It Have to Be Me?]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicalBasisIn Context triple: [Happy Hawaii, hasMusicalBasisIn, Why Did It Have to Be Me?]
-
A.
musicalBasisFor
chosen
Indicates that one musical work, idea, or element serves as the foundational source or inspiration upon which another musical work, idea, or element is built or derived.
-
B.
hasMusicalForm
Indicates that one entity (typically a musical work or piece) is characterized by or structured according to a particular musical form.
-
C.
hasMusical
Indicates that one entity features, includes, or is associated with a musical work, performance, or musical component.
-
D.
hasMusicalWorkType
Indicates that a musical work is associated with a specific type or category of musical composition.
-
E.
hasMusicalStyleCharacteristic
Indicates that something possesses or exhibits a particular musical style as a defining characteristic.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: May 1, 2026, 1:40 a.m.