Triple
T4685046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruby (character in "Ruby, Don’t Take Your Love to Town") |
E103899
|
entity |
| Predicate | songNarratorView |
P59007
|
FINISHED |
| Object | seen as unfaithful |
—
|
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: seen as unfaithful | Statement: [Ruby (character in "Ruby, Don’t Take Your Love to Town"), songNarratorView, seen as unfaithful]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: songNarratorView Context triple: [Ruby (character in "Ruby, Don’t Take Your Love to Town"), songNarratorView, seen as unfaithful]
-
A.
songAbout
Indicates that one entity (typically a song) has content, lyrics, or themes that are focused on, describe, or are dedicated to another entity.
-
B.
songFunction
Indicates the role or purpose a song serves within a larger context, such as a performance, narrative, or musical structure.
-
C.
hasLyricNarrator
Indicates that a musical or lyrical work is associated with a specific narrator who voices or presents its lyrics.
-
D.
sectionNarrator
Indicates that a given entity serves as the narrator or narrative voice for a particular section of a work.
-
E.
featuresSongwriter
Indicates that a musical work includes or credits a particular person as its songwriter.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
| PDg | Predicate description generation | batch_69bd67c895dc8190ba648002ff54424b |
completed | March 20, 2026, 3:29 p.m. |
Created at: March 20, 2026, 1:16 p.m.