Triple

T38569430
Position Surface form Disambiguated ID Type / Status
Subject Liquor City E929221 entity
Predicate hasChineseEquivalentName P54502 FINISHED
Object 酒城
酒城 is the Chinese name for Liquor City, a retail chain specializing in the sale of alcoholic beverages.
E2275434 NE FINISHED

How this triple was built (3 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: 酒城 | Statement: [Liquor City, hasChineseEquivalentName, 酒城]
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: 酒城
Triple: [Liquor City, hasChineseEquivalentName, 酒城]
Generated description
酒城 is the Chinese name for Liquor City, a retail chain specializing in the sale of alcoholic beverages.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasChineseEquivalentName
Context triple: [Liquor City, hasChineseEquivalentName, 酒城]
  • A. hasChineseNameComponent
    Indicates that an entity’s Chinese name includes a specific component, such as a particular character, syllable, or segment.
  • B. hasChineseNameType
    Indicates that an entity’s Chinese name belongs to a particular type or category (e.g., formal, short, transliterated).
  • C. hasEthnonymInChinese
    Indicates that an entity has a specific ethnonym (name for an ethnic group or people) expressed in the Chinese language.
  • D. hasChineseVersion chosen
    Indicates that an entity has a corresponding version or representation available in Chinese.
  • E. hasEnglishName
    Indicates that an entity is associated with a name expressed in the English language.
  • F. None of above.

Provenance (6 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_69f76ebd2248819083978362d81fa35e completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69ff5b233e9c8190adc06cca0758986b completed May 9, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41e04a1da081908a114568df484875 completed June 29, 2026, 3:02 a.m.
NEDg Description generation batch_6a41e41c47a4819080aad7cc077b3210 completed June 29, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a41e4bcdaac8190b53381cc8934bfab completed June 29, 2026, 3:21 a.m.
PD Predicate disambiguation batch_69ff5a5682108190a006b23c4fcdcc7c completed May 9, 2026, 4:01 p.m.
Created at: May 3, 2026, 4:32 p.m.