Triple
T17955099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Childhood |
E448924
|
entity |
| Predicate | hasAutobiographicalElementsFrom |
P19920
|
FINISHED |
| Object | Leo Tolstoy’s early life |
—
|
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: Leo Tolstoy’s early life | Statement: [Childhood, hasAutobiographicalElementsFrom, Leo Tolstoy’s early life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutobiographicalElementsFrom Context triple: [Childhood, hasAutobiographicalElementsFrom, Leo Tolstoy’s early life]
-
A.
hasAutobiographicalElements
chosen
Indicates that something, such as a work or narrative, contains elements drawn from the creator’s own life or personal experiences.
-
B.
hasAutobiographicalSubject
Indicates that something (such as a work, text, or narrative) has a subject that is the author or creator’s own life or personal experiences.
-
C.
hasPartInBiography
Indicates that a person or entity is featured or plays a role within someone’s biographical account.
-
D.
wroteAutobiographicalWork
Indicates that a person is the author of a written work that is an account of their own life.
-
E.
hasBiographicalStyle
Indicates that something is characterized by or presented in a biographical manner or style.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afaf1ddc8190b480147ac35a4912 |
completed | April 19, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.