Triple
T31400170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khyber Pass operations |
E800974
|
entity |
| Predicate | militaryTheaterType |
P1403
|
FINISHED |
| Object | mountain warfare |
—
|
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: mountain warfare | Statement: [Khyber Pass operations, militaryTheaterType, mountain warfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryTheaterType Context triple: [Khyber Pass operations, militaryTheaterType, mountain warfare]
-
A.
militaryTheater
Indicates that an entity is a geographic or operational area where military operations or campaigns are conducted.
-
B.
militaryTheaterCovered
Indicates that a specified military theater or area of operations falls within the geographic or operational scope covered by another entity (such as a plan, command, or agreement).
-
C.
militaryTheaterReportedOn
Indicates that a report or account has been made about a particular military theater or area of operations.
-
D.
fieldOfOperation
Indicates the domain, area, or scope within which an entity operates or carries out its primary activities.
-
E.
warfareType
chosen
Indicates the specific kind or category of warfare that characterizes a given conflict or military engagement.
- 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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 29, 2026, 9:19 p.m.