Triple
T12441948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Victor Hugo |
E297294
|
entity |
| Predicate | depictsFameLevel |
P27257
|
FINISHED |
| Object | internationally renowned author |
—
|
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: internationally renowned author | Statement: [Portrait of Victor Hugo, depictsFameLevel, internationally renowned author]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsFameLevel Context triple: [Portrait of Victor Hugo, depictsFameLevel, internationally renowned author]
-
A.
fameStatus
chosen
Indicates the level or state of public recognition or renown associated with an entity.
-
B.
famePeak
Indicates the time or point at which an entity reaches its highest level of fame or public recognition.
-
C.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
D.
depictsName
Indicates that something visually represents or portrays the name of an entity.
-
E.
depictsNotablePerson
Indicates that one entity visually represents or portrays a person who is considered notable or significant.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.