Triple

T31645914
Position Surface form Disambiguated ID Type / Status
Subject Chinese Sanlun school E807581 entity
Predicate textualCorpusName P95315 FINISHED
Object Sanlun (Three Treatises)
Sanlun (Three Treatises) is a foundational collection of Chinese Madhyamaka Buddhist texts that articulate the philosophy of emptiness and form the doctrinal basis of the Sanlun school.
 E1970943 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: Sanlun (Three Treatises) | Statement: [Chinese Sanlun school, textualCorpusName, Sanlun (Three Treatises)]
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: Sanlun (Three Treatises)
Triple: [Chinese Sanlun school, textualCorpusName, Sanlun (Three Treatises)]
Generated description
Sanlun (Three Treatises) is a foundational collection of Chinese Madhyamaka Buddhist texts that articulate the philosophy of emptiness and form the doctrinal basis of the Sanlun school.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: textualCorpusName
Context triple: [Chinese Sanlun school, textualCorpusName, Sanlun (Three Treatises)]
  • A. corpus
    Indicates that an entity is a collection or body of texts, documents, or linguistic data used as a unified set for analysis or reference.
  • B. hasTextualCorpus chosen
    Indicates that an entity is associated with or possesses a collection of written or textual materials.
  • C. primaryCorpusType
    Indicates the main or dominant type or category of corpus associated with an entity.
  • D. hasPartOfCorpus
    Indicates that one entity constitutes a component or segment of the overall corpus associated with another entity.
  • E. numberInCorpus
    Indicates the numerical count or frequency with which a given item appears within a specified corpus.
  • 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_69f348d9ce58819093ea2da83cbeeec1 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6abaa1f648190b77073771df3bf3b completed May 3, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79df559c819098e635fcb632e607 completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7a9bed2881908e5ca2d02afeaeff completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b3574f881908e98863d147351de completed June 12, 2026, 3:21 a.m.
PD Predicate disambiguation batch_69f6aa1e84b88190b025f6ca40f17a8a completed May 3, 2026, 1:51 a.m.
Created at: April 30, 2026, 10:51 p.m.