Triple
T4545704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabrielle Charpentier |
E110041
|
entity |
| Predicate | relativeLackOfDocumentation |
P18402
|
FINISHED |
| Object | compared to Georges Danton |
—
|
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: compared to Georges Danton | Statement: [Gabrielle Charpentier, relativeLackOfDocumentation, compared to Georges Danton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeLackOfDocumentation Context triple: [Gabrielle Charpentier, relativeLackOfDocumentation, compared to Georges Danton]
-
A.
hasLimitedDocumentation
chosen
Indicates that the subject is associated with documentation that is sparse, incomplete, or not sufficiently detailed.
-
B.
doesNotFullyExplain
Indicates that one entity’s explanation of another entity, event, or situation is incomplete or insufficient to account for it fully.
-
C.
languageOfDocumentation
Indicates the language in which the documentation for an entity is written or provided.
-
D.
typicallyLack
Indicates that one entity is characteristically or usually without, or does not possess, another entity or attribute.
-
E.
isPoorlyAttested
Indicates that there is limited, weak, or unreliable evidence or documentation supporting the existence, usage, or occurrence of the related item or relationship.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d761cc8190a7c8bdef6d130b5d |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.