Triple
T2988482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe DiMaggio |
E80686
|
entity |
| Predicate | mentionedInLyric |
P26173
|
FINISHED |
| Object | "Where have you gone, Joe DiMaggio?" |
—
|
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: "Where have you gone, Joe DiMaggio?" | Statement: [Joe DiMaggio, mentionedInLyric, "Where have you gone, Joe DiMaggio?"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentionedInLyric Context triple: [Joe DiMaggio, mentionedInLyric, "Where have you gone, Joe DiMaggio?"]
-
A.
scriptUsedInLyrics
Indicates that a particular writing system or script is used to write or represent the lyrics of a song or musical work.
-
B.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
C.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
D.
mentionedAs
chosen
Indicates that one entity is referred to or cited by name or description in the context of another entity.
-
E.
lyricFocus
Indicates that the primary emphasis or subject of the lyrics is centered on a particular entity or theme.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c9cdd081908fa8094a3ac1f8d3 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad961403108190bbecb8d3608fd4e0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.