Triple
T12441929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Victor Hugo |
E297294
|
entity |
| Predicate | depictsPersonDateOfDeath |
P20
|
FINISHED |
| Object | Victor Hugo 1885-05-22 |
—
|
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: Victor Hugo 1885-05-22 | Statement: [Portrait of Victor Hugo, depictsPersonDateOfDeath, Victor Hugo 1885-05-22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsPersonDateOfDeath Context triple: [Portrait of Victor Hugo, depictsPersonDateOfDeath, Victor Hugo 1885-05-22]
-
A.
dateOfDeath
chosen
Indicates the specific date on which an individual or entity died.
-
B.
yearOfDeath
Indicates the specific year in which an entity (typically a person or organism) died.
-
C.
honorsPersonDiedIn
Indicates that something serves as a tribute or commemoration to the person who died in a particular event, place, or circumstance.
-
D.
notableBearerDeathYear
Indicates the year in which a notable bearer of the referenced name, title, or role died.
-
E.
notablePersonDiedHere
Indicates that a notable or famous person died at the referenced location.
- 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.