Triple

T33667439
Position Surface form Disambiguated ID Type / Status
Subject YJ‑12 E862527 entity
Predicate alternateName P39 FINISHED
Object Eagle Strike‑12
Eagle Strike‑12 is a Chinese supersonic anti-ship cruise missile known for its high speed and sea-skimming attack profile.
E2061509 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: Eagle Strike‑12 | Statement: [YJ‑12, alternateName, Eagle Strike‑12]
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: Eagle Strike‑12
Triple: [YJ‑12, alternateName, Eagle Strike‑12]
Generated description
Eagle Strike‑12 is a Chinese supersonic anti-ship cruise missile known for its high speed and sea-skimming attack profile.

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_69f34984c4008190bb82f33a7819da64 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fa36f640819098051eff7e5a5787 completed May 3, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36272bb10c819086b9f54b05d0ae5e completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a3628199fe48190b534fd8a439d5855 completed June 20, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_6a3628b9d16481908e159baeeedd8c0d completed June 20, 2026, 5:44 a.m.
Created at: May 1, 2026, 1:42 a.m.