Triple
T35016933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simon & Marcy |
E1010078
|
entity |
| Predicate | focusesOnBackstoryOf |
P115645
|
FINISHED |
| Object | Simon Petrikov |
—
|
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: Simon Petrikov | Statement: [Simon & Marcy, focusesOnBackstoryOf, Simon Petrikov]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnBackstoryOf Context triple: [Simon & Marcy, focusesOnBackstoryOf, Simon Petrikov]
-
A.
expandsBackstoryOf
chosen
Indicates that one entity provides additional background details or context that elaborate on the history or origins of another entity.
-
B.
chronologicalBackstoryIn
Indicates that one event or narrative element serves as a prior backstory that occurs earlier in time within the timeline of another event or narrative.
-
C.
settingOfCharacterBackstory
Indicates the place or environment in which a character’s backstory events occur.
-
D.
hasKeyFigureInBackstory
Indicates that an entity’s background narrative prominently features a particular individual who significantly influences or shapes that backstory.
-
E.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.