Triple
T5122986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treaty of Schönbrunn |
E115513
|
entity |
| Predicate | imposedIndemnityAmount |
P19678
|
FINISHED |
| Object | 85 million francs |
—
|
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: 85 million francs | Statement: [Treaty of Schönbrunn, imposedIndemnityAmount, 85 million francs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imposedIndemnityAmount Context triple: [Treaty of Schönbrunn, imposedIndemnityAmount, 85 million francs]
-
A.
imposedWarIndemnityOn
Indicates that one party required another party to pay financial compensation as a penalty or reparation following a conflict or war.
-
B.
requiredIndemnityReceiver
Indicates that one party is obligated to provide indemnity (compensation or protection against loss) to another specified party.
-
C.
warIndemnityAmount
chosen
Indicates the amount of financial compensation required or paid as indemnity as a result of a war or armed conflict.
-
D.
authorizedBondAmount
Indicates the maximum bond value that has been formally approved or permitted for issuance or use in a given context.
-
E.
totalAidAmountAdjusted
Indicates the total amount of aid provided, after applying any relevant adjustments such as corrections, discounts, or recalculations.
- 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_69bd4442ade0819087b9461f892b206b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7d5a23908190a24e79d1b29d6fcf |
completed | March 20, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69bd77aa68b88190a50dd736a72d2901 |
completed | March 20, 2026, 4:36 p.m. |
Created at: March 20, 2026, 1:42 p.m.