Triple
T642069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armed Forces of the Republic of Poland |
E16759
|
entity |
| Predicate | hasProfessionalSoldiers |
P7256
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Armed Forces of the Republic of Poland, hasProfessionalSoldiers, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalSoldiers Context triple: [Armed Forces of the Republic of Poland, hasProfessionalSoldiers, true]
-
A.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
B.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
C.
hasMilitaryAdvisor
Indicates that one entity serves as a military advisor to another, providing guidance or expertise on military matters.
-
D.
maintainedPrivateArmy
Indicates that an entity kept and controlled its own private military force, separate from official or public armed forces.
-
E.
militaryCharacteristic
chosen
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f02bc2c8190b8a92b2505768c19 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0830008190a26ee158ed4dd1fe |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.