Triple
T604493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir Lenin |
E11564
|
entity |
| Predicate | portraitSubjectOf |
P1852
|
FINISHED |
| Object | Lenin statues and monuments worldwide |
—
|
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: Lenin statues and monuments worldwide | Statement: [Vladimir Lenin, portraitSubjectOf, Lenin statues and monuments worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraitSubjectOf Context triple: [Vladimir Lenin, portraitSubjectOf, Lenin statues and monuments worldwide]
-
A.
depictsPerson
chosen
Indicates that one entity visually represents or portrays a specific person.
-
B.
portraitArtist
Indicates that one entity is the artist who created a portrait depicting the other entity.
-
C.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
D.
notableWorkSubject
Indicates that a work is notably associated with a particular subject, such as a person, topic, or entity, as its primary focus or theme.
-
E.
facedBy
Indicates that one entity is oriented toward and directly opposite another entity, such that it is facing it.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e574444819087999404f3e3ffd9 |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49cf701e08190966d06b9ff4b582b |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.