Triple
T11150323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghanistan–United States relations |
E263766
|
entity |
| Predicate | U.S.militaryPresencePeakYear |
P81774
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [Afghanistan–United States relations, U.S.militaryPresencePeakYear, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: U.S.militaryPresencePeakYear Context triple: [Afghanistan–United States relations, U.S.militaryPresencePeakYear, 2010]
-
A.
USForceStrength
chosen
Indicates the level or magnitude of military forces deployed or available by the United States in a given context.
-
B.
numberOfDeployedMissilesPeak
Indicates the maximum number of missiles that were deployed at any point in time.
-
C.
hasMilitaryPresence
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
D.
hasLargestMilitaryPresenceInHawaii
Indicates that the subject entity maintains the greatest scale or extent of military forces or operations in Hawaii compared to all other entities.
-
E.
warTimeStrengthApprox
Indicates an approximate measure of an entity’s military strength or capacity during a time of war.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.