Triple
T991692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain John Byron |
E21404
|
entity |
| Predicate | genreOfNotability |
P4918
|
FINISHED |
| Object | Romantic literature (through his son Lord Byron) |
—
|
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: Romantic literature (through his son Lord Byron) | Statement: [Captain John Byron, genreOfNotability, Romantic literature (through his son Lord Byron)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfNotability Context triple: [Captain John Byron, genreOfNotability, Romantic literature (through his son Lord Byron)]
-
A.
genreSpecialty
Indicates that an entity specializes in or is particularly associated with a specific genre.
-
B.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
C.
notableCategory
chosen
Indicates that an entity is recognized as notable or significant within a particular category or classification.
-
D.
genreOfAppearance
Indicates the genre or type of creative work in which an entity appears.
-
E.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c25e5081909ff1ada6b8bf617a |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2adbde48190b07966d0c3179516 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.