Triple

T35375359
Position Surface form Disambiguated ID Type / Status
Subject Ma_MISS spectrometer E1021892 entity
Predicate acronym P43 FINISHED
Object Ma_MISS
Ma_MISS is a miniaturized infrared spectrometer designed for subsurface geological and mineralogical analysis on Mars rover missions.
E2139286 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: Ma_MISS | Statement: [Ma_MISS spectrometer, acronym, Ma_MISS]
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: Ma_MISS
Triple: [Ma_MISS spectrometer, acronym, Ma_MISS]
Generated description
Ma_MISS is a miniaturized infrared spectrometer designed for subsurface geological and mineralogical analysis on Mars rover missions.

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_69f76df000488190ab7c97f565677055 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7946395a08190af7599228f01749b completed May 3, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382cb75d4c8190a7967483d2b0225c completed June 21, 2026, 6:25 p.m.
NEDg Description generation batch_6a382f41151481909fff3701cd8d8605 completed June 21, 2026, 6:36 p.m.
NED2 Entity disambiguation (via description) batch_6a382fa19f2c8190b38af07e00e9e244 completed June 21, 2026, 6:38 p.m.
Created at: May 3, 2026, 4:03 p.m.