Triple

T2402152
Position Surface form Disambiguated ID Type / Status
Subject Mars Orbiter Mission E47792 entity
Predicate abbreviation P43 FINISHED
Object MOM
MOM is India’s first interplanetary spacecraft, a Mars orbiter launched by ISRO that made India the first Asian nation to reach Martian orbit.
 E262980 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: MOM | Statement: [Mars Orbiter Mission, abbreviation, MOM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MOM
Context triple: [Mars Orbiter Mission, abbreviation, MOM]
  • A. Mom
    Mom is a popular American sitcom starring Allison Janney and Anna Faris that follows a dysfunctional mother-daughter duo in recovery from addiction.
  • B. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • C. Mama
    "Mama" is a 1987 debut novel by Terry McMillan that follows a resilient Black single mother struggling to raise her children and rebuild her life amid poverty and personal turmoil.
  • D. Mama
    Mama is a key supporting character in the video game "Death Stranding," a brilliant yet tragic scientist who aids protagonist Sam Porter Bridges with her expertise in chiral technology.
  • E. Mothers
    Mothers is a section of the Tokyo Stock Exchange dedicated to emerging and high-growth startup companies seeking public investment.
  • 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: MOM
Triple: [Mars Orbiter Mission, abbreviation, MOM]
Generated description
MOM is India’s first interplanetary spacecraft, a Mars orbiter launched by ISRO that made India the first Asian nation to reach Martian orbit.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MOM
Target entity description: MOM is India’s first interplanetary spacecraft, a Mars orbiter launched by ISRO that made India the first Asian nation to reach Martian orbit.
  • A. Mom
    Mom is a popular American sitcom starring Allison Janney and Anna Faris that follows a dysfunctional mother-daughter duo in recovery from addiction.
  • B. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • C. Mama
    Mama is a key supporting character in the video game "Death Stranding," a brilliant yet tragic scientist who aids protagonist Sam Porter Bridges with her expertise in chiral technology.
  • D. Mama
    "Mama" is a 1987 debut novel by Terry McMillan that follows a resilient Black single mother struggling to raise her children and rebuild her life amid poverty and personal turmoil.
  • E. Mothers
    Mothers is a section of the Tokyo Stock Exchange dedicated to emerging and high-growth startup companies seeking public investment.
  • 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_69a88a1c450c81909f61abb8b6863885 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc8f623908190875fdbc95c944f33 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3e554c08190b5268c41ab34f4d9 completed March 9, 2026, 11:49 a.m.
NEDg Description generation batch_69aeb4a5011c8190bda6c487dab73131 completed March 9, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_69aeb59eb94c8190b36567fd38323986 completed March 9, 2026, 11:57 a.m.
Created at: March 4, 2026, 7:57 p.m.