Triple
T37725545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viola Pisani |
E939706
|
entity |
| Predicate | historicalContextOfStory |
P1409
|
FINISHED |
| Object | French Revolution |
E3314
|
NE 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: French Revolution | Statement: [Viola Pisani, historicalContextOfStory, French Revolution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalContextOfStory Context triple: [Viola Pisani, historicalContextOfStory, French Revolution]
-
A.
historicalNarrative
Indicates that one entity presents or constitutes a story or account about past events involving another entity.
-
B.
shareHistoricalContextAs
Indicates that two or more entities are associated with or understood within the same historical background, period, or circumstances.
-
C.
historicalContextOfWriting
Indicates that one entity provides the historical circumstances, period, or background in which another entity (typically a text or document) was written.
-
D.
historicalBackground
Indicates that one entity provides contextual historical information or circumstances that help explain the origin, development, or significance of another entity.
-
E.
hasHistoricalContext
chosen
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
- F. None of above.
Provenance (4 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01b3af7b908190b4675c85d32d106c |
completed | May 11, 2026, 10:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40d67fc37c8190a83025cf5028a3e6 |
completed | June 28, 2026, 8:08 a.m. |
| PD | Predicate disambiguation | batch_6a01b35813c081908e484b2b9ca5dd05 |
completed | May 11, 2026, 10:45 a.m. |
Created at: May 3, 2026, 4:18 p.m.