Triple
T5553508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexandra Lvovna Tolstaya |
E145581
|
entity |
| Predicate | mainSubjectOf |
P12980
|
FINISHED |
| Object | biographical works about the Tolstoy family |
—
|
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: biographical works about the Tolstoy family | Statement: [Alexandra Lvovna Tolstaya, mainSubjectOf, biographical works about the Tolstoy family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainSubjectOf Context triple: [Alexandra Lvovna Tolstaya, mainSubjectOf, biographical works about the Tolstoy family]
-
A.
primaryTopicOf
chosen
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
B.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
-
D.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
-
E.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ff9c9c48190b5e587d58c6515d8 |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b10bbf8819098655839c03b7832 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.