Triple
T28725757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cora Corman |
E730216
|
entity |
| Predicate | genreOfSongsInFiction |
P69570
|
FINISHED |
| Object | love songs |
—
|
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: love songs | Statement: [Cora Corman, genreOfSongsInFiction, love songs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfSongsInFiction Context triple: [Cora Corman, genreOfSongsInFiction, love songs]
-
A.
hasGenreInFiction
Indicates that a work of fiction belongs to or is categorized under a specific literary genre.
-
B.
musicalActivityInFiction
chosen
Indicates that a musical activity occurs within a fictional context or narrative rather than in real life.
-
C.
featuresFictionalMusical
Indicates that a work includes or prominently involves a fictional musical as part of its content or storyline.
-
D.
genreFunction
Indicates the role or purpose that a genre serves in relation to an entity, such as how it functions within classification, interpretation, or use.
-
E.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 5:55 a.m.