Triple
T15070339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Versailles arms limitations |
E379858
|
entity |
| Predicate | limitedArmySizeTo |
P13942
|
FINISHED |
| Object | 100000 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: 100000 soldiers | Statement: [Versailles arms limitations, limitedArmySizeTo, 100000 soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: limitedArmySizeTo Context triple: [Versailles arms limitations, limitedArmySizeTo, 100000 soldiers]
-
A.
restrictedArmySizeOf
chosen
Indicates that one entity imposes a limitation or cap on the allowable size of another entity’s army.
-
B.
soldiersCapacity
Indicates the maximum number of soldiers that an entity can hold, support, or accommodate.
-
C.
limitedNumberOfMembers
Indicates that the associated group or entity has a maximum allowed number of members or participants.
-
D.
militarySize
Indicates the total number of personnel in a military force, typically including active-duty members and sometimes reserves.
-
E.
hasApproximateDefendingForceSize
Indicates that an entity is associated with a defending force whose size is known only approximately rather than as an exact value.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7f86df48190b3a2cf441fefb477 |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:02 a.m.