Triple

T9808383
Position Surface form Disambiguated ID Type / Status
Subject Terrain Mapping Camera 2 E238207 entity
Predicate abbreviation P43 FINISHED
Object TMC 2
TMC 2 is a high-resolution terrain mapping camera used on Indian lunar missions to capture detailed three-dimensional images of the Moon’s surface.
 E822844 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: TMC 2 | Statement: [Terrain Mapping Camera 2, abbreviation, TMC 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TMC 2
Context triple: [Terrain Mapping Camera 2, abbreviation, TMC 2]
  • A. TMC
    TMC is the commonly used abbreviation for Thurgood Marshall College, one of the undergraduate colleges at the University of California, San Diego.
  • B. TMC
    TMC is a commonly used abbreviation for the Indian city of Thane, particularly in the context of its municipal corporation and local governance.
  • C. TMC
    TMC is a French television channel specializing in general entertainment programming, owned by the TF1 Group.
  • D. TMC
    TMC is a major Indian political party, formally known as the All India Trinamool Congress, primarily influential in the state of West Bengal.
  • E. TMB 2000 series
    The TMB 2000 series is a class of electric multiple unit trains used on the Barcelona Metro, designed for high-capacity urban rapid transit service.
  • 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: TMC 2
Triple: [Terrain Mapping Camera 2, abbreviation, TMC 2]
Generated description
TMC 2 is a high-resolution terrain mapping camera used on Indian lunar missions to capture detailed three-dimensional images of the Moon’s surface.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TMC 2
Target entity description: TMC 2 is a high-resolution terrain mapping camera used on Indian lunar missions to capture detailed three-dimensional images of the Moon’s surface.
  • A. TMC
    TMC is the commonly used abbreviation for Thurgood Marshall College, one of the undergraduate colleges at the University of California, San Diego.
  • B. TMC
    TMC is a commonly used abbreviation for the Indian city of Thane, particularly in the context of its municipal corporation and local governance.
  • C. TMC
    TMC is a French television channel specializing in general entertainment programming, owned by the TF1 Group.
  • D. TMC
    TMC is a major Indian political party, formally known as the All India Trinamool Congress, primarily influential in the state of West Bengal.
  • E. TMB 2000 series
    The TMB 2000 series is a class of electric multiple unit trains used on the Barcelona Metro, designed for high-capacity urban rapid transit service.
  • 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb21ef32c8190ab4b09d157798451 completed April 2, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc5b4dd8819088c86946b4eb8a39 completed April 5, 2026, 2:43 a.m.
NEDg Description generation batch_69d1cd7f41448190b387109235dbc7f5 completed April 5, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69d1cdefca5c8190a673caca42aaa7d0 completed April 5, 2026, 2:50 a.m.
Created at: March 30, 2026, 8:29 p.m.