Triple
T29033750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Grayson |
E737796
|
entity |
| Predicate | fictionalBrother |
P188780
|
FINISHED |
| Object | Daniel Grayson |
—
|
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: Daniel Grayson | Statement: [Charlotte Grayson, fictionalBrother, Daniel Grayson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalBrother Context triple: [Charlotte Grayson, fictionalBrother, Daniel Grayson]
-
A.
fictionalSon
Indicates that one entity is portrayed as the son of another entity within a fictional or narrative context.
-
B.
fictionalUncle
Indicates that one entity is the uncle of another within a fictional or narrative context.
-
C.
fictionalHalfSibling
Indicates that one entity is considered a half-sibling of another within a fictional or narrative context, sharing one parent in the story’s canon.
-
D.
isFictionalTwinOf
Indicates that one entity is the imagined or fictional twin counterpart of another entity, typically within a narrative or creative context.
-
E.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbad1b3ba08190ad69e21461333f2e |
completed | May 6, 2026, 9:05 p.m. |
Created at: April 28, 2026, 9:57 a.m.