Triple

T5126040
Position Surface form Disambiguated ID Type / Status
Subject Mars Reconnaissance Orbiter E115585 entity
Predicate instrument P792 FINISHED
Object CTX
CTX is a high-resolution context camera aboard NASA’s Mars Reconnaissance Orbiter used to image and map the Martian surface.
 E495756 NE FINISHED

How this triple was built (4 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: CTX | Statement: [Mars Reconnaissance Orbiter, instrument, CTX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CTX
Context triple: [Mars Reconnaissance Orbiter, instrument, CTX]
  • A. TC
    TC is the common abbreviation for the Trilateral Commission, a non-governmental policy discussion group that brings together leaders from North America, Europe, and Asia to address global issues.
  • B. TC
    TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • C. TC
    TC is the Constitutional Court of Peru, the country’s highest body responsible for interpreting and safeguarding the constitution and constitutional rights.
  • D. TC
    TC is the commonly used abbreviation for Transport Canada, the federal department responsible for transportation policies and programs in Canada.
  • E. TC
    TC is the two-letter ISO 3166-1 alpha-2 country code assigned to the Turks and Caicos Islands.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: CTX
Triple: [Mars Reconnaissance Orbiter, instrument, CTX]
Generated description
CTX is a high-resolution context camera aboard NASA’s Mars Reconnaissance Orbiter used to image and map the Martian surface.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CTX
Target entity description: CTX is a high-resolution context camera aboard NASA’s Mars Reconnaissance Orbiter used to image and map the Martian surface.
  • A. TC
    TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
  • B. TC
    TC is the common abbreviation for the Trilateral Commission, a non-governmental policy discussion group that brings together leaders from North America, Europe, and Asia to address global issues.
  • C. TC
    TC is the commonly used abbreviation for Transport Canada, the federal department responsible for transportation policies and programs in Canada.
  • D. TC
    TC is the two-letter ISO 3166-1 alpha-2 country code assigned to the Turks and Caicos Islands.
  • E. TC
    TC is the Constitutional Court of Peru, the country’s highest body responsible for interpreting and safeguarding the constitution and constitutional rights.
  • F. None of above. chosen

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_69bd444426bc819099ccd23f141e22aa completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd78228b2081908c70efd3db71f8d4 completed March 20, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec4bb52fc8190b4c0cd6bc367e8eb completed March 21, 2026, 4:18 p.m.
NEDg Description generation batch_69bec562d0508190851b5a3307e9405b completed March 21, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69bec6478b848190bc09d7f6485681b4 completed March 21, 2026, 4:24 p.m.
Created at: March 20, 2026, 1:42 p.m.