Triple

T32573090
Position Surface form Disambiguated ID Type / Status
Subject Gaofen-4 E832566 entity
Predicate targetRegion P860 FINISHED
Object China E5561 NE FINISHED

How this triple was built (1 step)

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: China | Statement: [Gaofen-4, targetRegion, China]

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_69f34927bb308190ad94da1b11cad13c completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c63ca2e881909f8e056c1ed181ba completed May 3, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349291cc9081909a7fdfb6b016311f completed June 19, 2026, 12:51 a.m.
Created at: May 1, 2026, 1:04 a.m.