Triple

T2293366
Position Surface form Disambiguated ID Type / Status
Subject Apollo Lunar Module E51554 entity
Predicate abbreviation P43 FINISHED
Object LM
LM is the Apollo Lunar Module, the spacecraft used by NASA during the Apollo program to land astronauts on the Moon and return them to lunar orbit.
 E254492 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: LM | Statement: [Apollo Lunar Module, abbreviation, LM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LM
Context triple: [Apollo Lunar Module, abbreviation, LM]
  • A. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • B. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • C. LC
    LC is the second-generation Holden Torana series produced in the late 1960s and early 1970s, notable for introducing six-cylinder performance variants in the compact Australian car lineup.
  • D. LC
    LC is the two-letter ISO 3166-1 alpha-2 country code assigned to Saint Lucia.
  • E. LK
    LK is the two-letter ISO 3166-1 alpha-2 country code assigned to Sri Lanka for international standardization and identification purposes.
  • 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: LM
Triple: [Apollo Lunar Module, abbreviation, LM]
Generated description
LM is the Apollo Lunar Module, the spacecraft used by NASA during the Apollo program to land astronauts on the Moon and return them to lunar orbit.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LM
Target entity description: LM is the Apollo Lunar Module, the spacecraft used by NASA during the Apollo program to land astronauts on the Moon and return them to lunar orbit.
  • A. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • B. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • C. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • D. LC
    LC is the second-generation Holden Torana series produced in the late 1960s and early 1970s, notable for introducing six-cylinder performance variants in the compact Australian car lineup.
  • E. LC
    LC is the two-letter ISO 3166-1 alpha-2 country code assigned to Saint Lucia.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5d90d988190b3253b54e5bb5530 completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f23ca34819091d2bb0d41613b4a completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae82aa6d7c81909cb770ea2be10b2a completed March 9, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae837e392c8190baa7552ce8c14995 completed March 9, 2026, 8:23 a.m.
Created at: March 4, 2026, 7:48 p.m.