Triple
T1003757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elba |
E21661
|
entity |
| Predicate | NapoleonTitleWhileThere |
P22205
|
FINISHED |
| Object | Emperor of Elba |
—
|
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: Emperor of Elba | Statement: [Elba, NapoleonTitleWhileThere, Emperor of Elba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NapoleonTitleWhileThere Context triple: [Elba, NapoleonTitleWhileThere, Emperor of Elba]
-
A.
securityStatusDuringNapoleonExile
Indicates the security conditions or measures in place during the period of Napoleon’s exile.
-
B.
startTimeOfUseByNapoleon
Indicates the point in time when Napoleon began using or employing something.
-
C.
endTimeOfUseByNapoleon
Indicates the point in time when Napoleon’s use or control of something came to an end.
-
D.
builtDuringReignOf
Indicates that something was constructed while a particular ruler or authority was in power.
-
E.
successorAsEmpressOfTheFrench
Indicates that one person became the next Empress of the French following another person in that imperial role.
- F. None of above. chosen
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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4ff614081909478500ada1f5059 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.