Triple

T1945994
Position Surface form Disambiguated ID Type / Status
Subject Austroasiatic E42054 entity
Predicate comparativeLinguistics P19895 FINISHED
Object subject of extensive reconstruction LITERAL FINISHED

How this triple was built (2 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: subject of extensive reconstruction | Statement: [Austroasiatic, comparativeLinguistics, subject of extensive reconstruction]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: comparativeLinguistics
Context triple: [Austroasiatic, comparativeLinguistics, subject of extensive reconstruction]
  • A. historicalLinguistics chosen
    Indicates the study of how languages change over time and the relationships between earlier and later language forms.
  • B. hasLinguisticTypology
    Indicates a relationship where a language or linguistic system is characterized by a specific typological classification or structural type.
  • C. linguisticField
    Indicates that something pertains to or is associated with a particular area or subdiscipline within linguistics.
  • D. linguisticClassification
    Indicates the relationship by which an entity is categorized according to its language or linguistic type.
  • E. ancientLanguages
    Indicates that the related entities are languages that originated in and were used during ancient historical periods.
  • F. None of above.

Provenance (3 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb32ebae881908f7541301f0198ae completed March 7, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69abaff25a588190bb4cbc8df9fc6d64 completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:36 p.m.