Triple
T27810479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mystic Manor |
E702504
|
entity |
| Predicate | backstoryCharacter |
P153273
|
FINISHED |
| Object | Lord Henry Mystic |
—
|
NE NERFINISHED |
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: Lord Henry Mystic | Statement: [Mystic Manor, backstoryCharacter, Lord Henry Mystic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: backstoryCharacter Context triple: [Mystic Manor, backstoryCharacter, Lord Henry Mystic]
-
A.
protagonistBackground
Indicates that one entity serves as the background, history, or prior circumstances of the protagonist entity in a narrative or story.
-
B.
roleInCharacterBackstory
Indicates that one entity plays a specific role or part in shaping another entity’s character backstory or personal history.
-
C.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
-
D.
expandsBackstoryOf
Indicates that one entity provides additional background details or context that elaborate on the history or origins of another entity.
-
E.
aboutFictionalCharacter
chosen
Indicates that something (such as a work, statement, or discussion) concerns or is centered on a fictional character.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6383da0e08190a4e394aba4b49348 |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 5:42 p.m.