Triple

T32690592
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Advanced Surface to Air Missile System E835845 entity
Predicate usesMissile P20224 FINISHED
Object AMRAAM-ER
AMRAAM-ER is an extended-range variant of the AIM-120 AMRAAM air-to-air missile adapted for enhanced ground-based air defense against aircraft and cruise missiles.
E6292 NE 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: AMRAAM-ER | Statement: [Norwegian Advanced Surface to Air Missile System, usesMissile, AMRAAM-ER]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: AMRAAM-ER
Triple: [Norwegian Advanced Surface to Air Missile System, usesMissile, AMRAAM-ER]
Generated description
AMRAAM-ER is an extended-range variant of the AIM-120 AMRAAM air-to-air missile adapted for enhanced ground-based air defense against aircraft and cruise missiles.

Provenance (5 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_69f3493211388190993801216afbc2a7 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c819ff548190aa800cc795b11e14 completed May 3, 2026, 3:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34a79ed2c0819098237939cd0b6d1b completed June 19, 2026, 2:21 a.m.
NEDg Description generation batch_6a34a88662148190b818f297a90e1a93 completed June 19, 2026, 2:25 a.m.
NED2 Entity disambiguation (via description) batch_6a34a92a11748190a6205eb616f5b475 completed June 19, 2026, 2:27 a.m.
Created at: May 1, 2026, 1:09 a.m.