Triple
T948679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Corps |
E20470
|
entity |
| Predicate | hasTypicalRole |
P18942
|
FINISHED |
| Object | conduct offensive operations |
—
|
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: conduct offensive operations | Statement: [Army Corps, hasTypicalRole, conduct offensive operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalRole Context triple: [Army Corps, hasTypicalRole, conduct offensive operations]
-
A.
typicalRole
chosen
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
B.
hasMainRole
Indicates that an entity holds the primary or most significant role in relation to another entity or context.
-
C.
hasCapitalRole
Indicates that an entity holds an official role, function, or status specifically associated with a capital city.
-
D.
servesRole
Indicates that one entity performs, fulfills, or occupies a particular function, position, or responsibility in relation to another entity.
-
E.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bf9bb88190a79b2db698613a8d |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29f05f481908814bd11f235e9d0 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.