Triple
T23138899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My One and Only |
E577401
|
entity |
| Predicate | usesLyrics |
P18290
|
FINISHED |
| Object | classic Ira Gershwin lyrics |
—
|
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: classic Ira Gershwin lyrics | Statement: [My One and Only, usesLyrics, classic Ira Gershwin lyrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLyrics Context triple: [My One and Only, usesLyrics, classic Ira Gershwin lyrics]
-
A.
hasLyric
chosen
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasLyricsFeature
Indicates that something possesses a particular characteristic or attribute related to its lyrics.
-
C.
hasLyricsIn
Indicates that the lyrics of a work are written or available in a specified language.
-
D.
hasExplicitLyrics
Indicates that the referenced content contains explicit language or themes, such as profanity, sexual content, or strong violence.
-
E.
hasAdditionalLyrics
Indicates that an entity (such as a song or track) includes extra or supplementary lyrics beyond a primary or original set.
- 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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e8e23988190814524f63a7efe36 |
completed | April 29, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4 p.m.