Triple

T3063657
Position Surface form Disambiguated ID Type / Status
Subject Lifetime E62053 entity
Predicate hasSisterChannel P6991 FINISHED
Object LMN
LMN is an American cable television network, formerly known as Lifetime Movie Network, that primarily airs made-for-TV movies and films targeted toward a female audience.
 E323296 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: LMN | Statement: [Lifetime, hasSisterChannel, LMN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LMN
Context triple: [Lifetime, hasSisterChannel, LMN]
  • A. MNP
    MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
  • 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. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • D. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • E. 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.
  • 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: LMN
Triple: [Lifetime, hasSisterChannel, LMN]
Generated description
LMN is an American cable television network, formerly known as Lifetime Movie Network, that primarily airs made-for-TV movies and films targeted toward a female audience.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LMN
Target entity description: LMN is an American cable television network, formerly known as Lifetime Movie Network, that primarily airs made-for-TV movies and films targeted toward a female audience.
  • A. MNP
    MNP is the three-letter ISO 3166-1 alpha-3 country code assigned to the Northern Mariana Islands.
  • 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. LMA
    LMA is the League Managers Association, the professional body representing and supporting football managers in English leagues.
  • D. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • E. 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.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9ea088fc819090b9d5bbcb268671 completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef118cb48190a1f666ead7c19a12 completed March 11, 2026, 10:39 p.m.
NEDg Description generation batch_69b1f1291670819083866bd4950d4124 completed March 11, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_69b1f1990be08190bfa83c08323c5d40 completed March 11, 2026, 10:50 p.m.
Created at: March 8, 2026, 3:02 p.m.