Triple
T27064673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Treaty of Paris |
E685140
|
entity |
| Predicate | limitedFrenchArmyTo |
P164487
|
FINISHED |
| Object | 150000 soldiers |
—
|
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: 150000 soldiers | Statement: [First Treaty of Paris, limitedFrenchArmyTo, 150000 soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: limitedFrenchArmyTo Context triple: [First Treaty of Paris, limitedFrenchArmyTo, 150000 soldiers]
-
A.
FrenchUnit
Indicates that a unit or entity is associated with France, typically by origin, affiliation, or national identity.
-
B.
involvedFrenchTroops
Indicates that the event, action, or situation included the participation or presence of French military forces.
-
C.
outcomeForFrenchForces
Indicates the result or consequence experienced by the French forces in a given event or engagement.
-
D.
frenchTroopsEvacuated
Indicates that French military forces withdrew or were removed from a particular location or situation.
-
E.
FrenchCasualties
Indicates that the relationship specifies the number or extent of casualties suffered by French forces in a given event or context.
- 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_69ef14835fcc81908bd737b4267ae528 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f64e6e8c9081908ce4d364aa26147a |
completed | May 2, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64db8ee1881909362701d72ffe282 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 27, 2026, 8:24 a.m.