Triple
T26272933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth of Bohemia |
E660478
|
entity |
| Predicate | correspondenceTopic |
P103055
|
FINISHED |
| Object | passions and emotions |
—
|
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: passions and emotions | Statement: [Elizabeth of Bohemia, correspondenceTopic, passions and emotions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondenceTopic Context triple: [Elizabeth of Bohemia, correspondenceTopic, passions and emotions]
-
A.
relatedCorrespondence
Indicates that there exists a piece of correspondence (such as a letter, email, or message) that is associated with or pertains to the related entity.
-
B.
topicOfDialogue
Indicates that a particular subject or theme is the main focus of a dialogue or conversation between entities.
-
C.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
D.
correspondedWith
Indicates that two entities engaged in mutual communication, typically by exchanging messages or letters over a period of time.
-
E.
coveredTopics
chosen
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
- 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_69ee812960d081909cff6085cc9fa3a6 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f638d11c988190af7fd4572b08e038 |
completed | May 2, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69f63706b6008190993577193c85ff50 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 26, 2026, 9:52 p.m.