Triple
T4668704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Treaty of Paris |
E102908
|
entity |
| Predicate | indemnityAmount |
P19678
|
FINISHED |
| Object | 700 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: 700 million francs | Statement: [Second Treaty of Paris, indemnityAmount, 700 million francs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indemnityAmount Context triple: [Second Treaty of Paris, indemnityAmount, 700 million francs]
-
A.
warIndemnityAmount
chosen
Indicates the amount of financial compensation required or paid as indemnity as a result of a war or armed conflict.
-
B.
requiredIndemnityReceiver
Indicates that one party is obligated to provide indemnity (compensation or protection against loss) to another specified party.
-
C.
authorizedBondAmount
Indicates the maximum bond value that has been formally approved or permitted for issuance or use in a given context.
-
D.
statutoryLimitPerIncidentUSD
Indicates the maximum monetary amount, in U.S. dollars, that is legally allowed to be claimed or paid for a single incident under a specific statute or regulation.
-
E.
reparationAmountPerPerson
Indicates the specific amount of reparations allocated or owed to each individual person involved.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd655aceb081908100ffc0498fe183 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6215864c8190b50ba0f63ba87d0c |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.