Triple
T4817008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praskovya Fyodorovna |
E107611
|
entity |
| Predicate | reactionToIvanIlyichDeath |
P17673
|
FINISHED |
| Object | focus on pension and legal matters |
—
|
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: focus on pension and legal matters | Statement: [Praskovya Fyodorovna, reactionToIvanIlyichDeath, focus on pension and legal matters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reactionToIvanIlyichDeath Context triple: [Praskovya Fyodorovna, reactionToIvanIlyichDeath, focus on pension and legal matters]
-
A.
viewOfDeath
Indicates a subject’s beliefs, attitudes, or conceptual understanding regarding death.
-
B.
containsDeathOf
Indicates that the subject includes, depicts, or involves the death of the referenced entity.
-
C.
death
Indicates the event or state in which an entity ceases to live or exist, marking the end of its biological or functional processes.
-
D.
deathDescribedAs
Indicates that one entity characterizes, portrays, or refers to another entity’s death using a particular description, metaphor, or wording.
-
E.
associatedWithDeathOf
chosen
Indicates a relationship where one entity is connected in some relevant way to the death of another entity, such as by involvement, causation, or contextual association.
- 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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.