Triple
T20277278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Mantua (1796–1797) |
E503047
|
entity |
| Predicate | aimOfFrench |
P15014
|
FINISHED |
| Object | force Austrian capitulation in Italy |
—
|
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: force Austrian capitulation in Italy | Statement: [Siege of Mantua (1796–1797), aimOfFrench, force Austrian capitulation in Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimOfFrench Context triple: [Siege of Mantua (1796–1797), aimOfFrench, force Austrian capitulation in Italy]
-
A.
primaryObjectiveOfFrench
Indicates that something is the main or foremost goal, aim, or purpose associated with France or French entities.
-
B.
objectiveOfFrance
chosen
Indicates that something is an objective, goal, or aim pursued by France.
-
C.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
-
D.
frenchAim
Indicates that an entity’s goal, intention, or target is specifically related to France, the French language, or French culture.
-
E.
significanceForFrance
Indicates that something holds particular importance, impact, or relevance specifically in the context of France.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e675e4cdfc81908c7cb4519a7d744b |
completed | April 20, 2026, 6:52 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 10:35 a.m.