Triple
T5397386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Fleurs du mal |
E120689
|
entity |
| Predicate | resultOfTrial |
P47971
|
FINISHED |
| Object | six poems banned by French court |
—
|
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: six poems banned by French court | Statement: [Les Fleurs du mal, resultOfTrial, six poems banned by French court]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultOfTrial Context triple: [Les Fleurs du mal, resultOfTrial, six poems banned by French court]
-
A.
outcomeOfTrial
chosen
Indicates that a particular result or verdict is produced as the consequence of a specific trial or legal proceeding.
-
B.
outcomeOf
Indicates that one entity is the result, consequence, or product that arises from another entity, event, or process.
-
C.
result
Indicates that one entity is produced, caused, or brought about as an outcome or consequence of another entity or process.
-
D.
resultDetermination
Indicates the process or criteria by which an outcome, decision, or result is established or concluded from given inputs or conditions.
-
E.
trial
Indicates that an entity is the subject of a legal or formal judicial proceeding to determine guilt, liability, or resolution of a dispute.
- 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.