Triple

T4048235
Position Surface form Disambiguated ID Type / Status
Subject Lasi E84119 entity
Predicate partOf P40 FINISHED
Object Sindhi language E12831 NE 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: Sindhi language | Statement: [Lasi, partOf, Sindhi language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sindhi language
Context triple: [Lasi, partOf, Sindhi language]
  • A. Sindhi chosen
    Sindhi is an Indo-Aryan language spoken primarily in Pakistan and India, known for its rich literary tradition and distinct script variants.
  • B. Urdu language
    Urdu is a major South Asian language, written in a Perso-Arabic script and widely used in Pakistan and parts of India in literature, media, and everyday communication.
  • C. Saraiki
    Saraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • D. Pashto language
    Pashto is an Eastern Iranian language spoken primarily in Afghanistan and Pakistan, serving as one of Afghanistan’s official languages and a key marker of Pashtun ethnic identity.
  • E. Punjabi language
    Punjabi language is an Indo-Aryan language widely spoken in the Punjab region of India and Pakistan and among large diaspora communities worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb81040481909b22e4c445ecae0f completed March 9, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589ccd0a48190b98dbe7268df678f completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:37 p.m.