Triple
T383461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gothic literature |
E8728
|
entity |
| Predicate | hasTypicalCharacterType |
P10724
|
FINISHED |
| Object | Byronic hero |
—
|
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: Byronic hero | Statement: [Gothic literature, hasTypicalCharacterType, Byronic hero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCharacterType Context triple: [Gothic literature, hasTypicalCharacterType, Byronic hero]
-
A.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
B.
characterSetType
Indicates the type or category of character set associated with or used by an entity.
-
C.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
D.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
E.
typicalKey
Indicates that the referenced key is the standard or most commonly used key associated with an entity or context.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec40ff8c81909306eb2dfe1512af |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96602188190b0cbc167f55a9237 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.