Triple

T26629283
Position Surface form Disambiguated ID Type / Status
Subject IRDIS E668446 entity
Predicate hasFilter P42116 FINISHED
Object K band
K band is a near-infrared wavelength range commonly used in astronomy for observing celestial objects through dust and gas with reduced extinction.
E1734872 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: K band | Statement: [IRDIS, hasFilter, K band]
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: K band
Triple: [IRDIS, hasFilter, K band]
Generated description
K band is a near-infrared wavelength range commonly used in astronomy for observing celestial objects through dust and gas with reduced extinction.

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_69ee9cff507c819092b95bf7219a702e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615ec89f081909007ddbe9d99f074 completed May 2, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec3663e881908ea934e45c990b7c completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11ecc2d59c8190812339ba67cc0549 completed May 23, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_6a11ed49546081908d4553f4ceab71ab completed May 23, 2026, 6:09 p.m.
Created at: April 27, 2026, 2:24 a.m.