Triple
T11668723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Young Romance |
E277319
|
entity |
| Predicate | helpedEstablishGenre |
P22766
|
FINISHED |
| Object | romance comics |
—
|
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: romance comics | Statement: [Young Romance, helpedEstablishGenre, romance comics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpedEstablishGenre Context triple: [Young Romance, helpedEstablishGenre, romance comics]
-
A.
hasGenreInfluenceOn
chosen
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
B.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
C.
usedGenre
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
D.
workedOnGenre
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
E.
hasGenreOrigin
Indicates that a genre originates from, or has its roots in, a particular source, place, culture, or tradition.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a440d8a481909a13c97813408bc8 |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:39 p.m.