Triple
T4452741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodnight Irene |
E97650
|
entity |
| Predicate | hasLyricNarrator |
P56604
|
FINISHED |
| Object | first-person male narrator |
—
|
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: first-person male narrator | Statement: [Goodnight Irene, hasLyricNarrator, first-person male narrator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLyricNarrator Context triple: [Goodnight Irene, hasLyricNarrator, first-person male narrator]
-
A.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasNarration
Indicates that an entity provides spoken or written commentary or storytelling for another entity, such as a work, event, or scene.
-
C.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
D.
hasVariableLyrics
Indicates that the lyrics of a song or musical piece change between different performances, versions, or contexts.
-
E.
hasLyricalRegister
Indicates that something (such as a text, utterance, or expression) is associated with a particular lyrical or stylistic register in language.
- F. None of above. chosen
Provenance (4 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355f49dc081908727af81b886c08d |
completed | March 13, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69b34f649df081909d3cc2f6a1b8f282 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b354e1f0948190b645096b2b7037af |
completed | March 13, 2026, 12:05 a.m. |
Created at: March 12, 2026, 11:33 p.m.