Triple

T9422238
Position Surface form Disambiguated ID Type / Status
Subject Thout E227180 entity
Predicate alternativeTransliteration P5923 FINISHED
Object Tout
Tout is an alternative transliteration of Thout, the first month of the ancient Egyptian and Coptic calendars.
 E798464 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: Tout | Statement: [Thout, alternativeTransliteration, Tout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tout
Context triple: [Thout, alternativeTransliteration, Tout]
  • A. Tous
    Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
  • B. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • C. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • D. Barcha
    Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
  • E. Toinette
    Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
  • 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: Tout
Triple: [Thout, alternativeTransliteration, Tout]
Generated description
Tout is an alternative transliteration of Thout, the first month of the ancient Egyptian and Coptic calendars.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tout
Target entity description: Tout is an alternative transliteration of Thout, the first month of the ancient Egyptian and Coptic calendars.
  • A. Tous
    Tous is a Spanish jewelry and accessories brand known for its distinctive teddy bear logo and affordable luxury designs.
  • B. Tanto
    Tanto was a former town in Hyōgo Prefecture, Japan, that later became part of the expanded city of Toyooka through municipal merger.
  • C. Tyto
    Tyto is a genus of medium-sized owls best known for including the widespread barn owl and its close relatives.
  • D. Barcha
    Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
  • E. Toinette
    Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd6c2651c48190808281779fab49df completed April 1, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107d290148190855b8d50eb80c591 completed April 4, 2026, 12:45 p.m.
NEDg Description generation batch_69d108d87adc8190b602c115c09650d6 completed April 4, 2026, 12:49 p.m.
NED2 Entity disambiguation (via description) batch_69d10995e3bc8190a8db18e4ed0fc261 completed April 4, 2026, 12:52 p.m.
Created at: March 30, 2026, 7:48 p.m.