Triple
T30941008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleeping Beauty legend |
E788259
|
entity |
| Predicate | earlierRelatedTale |
P102058
|
FINISHED |
| Object | Sun, Moon, and Talia |
—
|
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: Sun, Moon, and Talia | Statement: [Sleeping Beauty legend, earlierRelatedTale, Sun, Moon, and Talia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earlierRelatedTale Context triple: [Sleeping Beauty legend, earlierRelatedTale, Sun, Moon, and Talia]
-
A.
associatedTale
chosen
Indicates that one entity is linked or connected to a particular tale, story, or narrative.
-
B.
alsoRelatedParable
Indicates that one parable is additionally related to another parable beyond the primary or most obvious connection.
-
C.
originStoryIncludes
Indicates that an entity’s origin story contains, involves, or features the referenced element as a component or part of that backstory.
-
D.
hasSiblingInStory
Indicates that one character in a narrative has at least one sibling who also appears within the same story.
-
E.
retellsStoryOf
Indicates that one entity recounts or narrates the story originally told or experienced by another entity.
- 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 29, 2026, 8:53 p.m.