Triple
T33400568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarbadar state |
E855284
|
entity |
| Predicate | typeOfMilitary |
P81775
|
FINISHED |
| Object | irregular militia |
—
|
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: irregular militia | Statement: [Sarbadar state, typeOfMilitary, irregular militia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMilitary Context triple: [Sarbadar state, typeOfMilitary, irregular militia]
-
A.
hasMilitaryType
chosen
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
B.
civilOrMilitary
Indicates that something is classified as either civil (non-military) or military in nature or function.
-
C.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
D.
armedForcesCategory
Indicates the classification of a country's or group's military forces into a specific type or category (e.g., army, navy, air force, paramilitary).
-
E.
militaryTrainingType
Indicates the specific kind or category of military training associated with an entity or event.
- 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_69f3496e3f1c8190bcecfa82aa9d17ff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00b34364448190b8c9948d5a24d845 |
completed | May 10, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_6a00b2e4f13c819081bac7d763c414ad |
completed | May 10, 2026, 4:31 p.m. |
Created at: May 1, 2026, 1:35 a.m.