Triple

T11652341
Position Surface form Disambiguated ID Type / Status
Subject PSX E276933 entity
Predicate flagshipIndex P9819 FINISHED
Object KSE-100 Index E276935 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: KSE-100 Index | Statement: [PSX, flagshipIndex, KSE-100 Index]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KSE-100 Index
Context triple: [PSX, flagshipIndex, KSE-100 Index]
  • A. KSE-100 Index chosen
    The KSE-100 Index is Pakistan’s benchmark stock market index, tracking the performance of the largest and most liquid companies listed on the Pakistan Stock Exchange.
  • B. KSE-30 Index
    The KSE-30 Index is a benchmark stock market index in Pakistan that tracks the performance of 30 of the largest and most liquid companies listed on the Pakistan Stock Exchange.
  • C. KMI All Share Index
    The KMI All Share Index is a broad stock market index that tracks the performance of all listed companies on the Pakistan Stock Exchange.
  • D. SSE Composite Index
    The SSE Composite Index is a major Chinese stock market index that tracks the performance of all stocks listed on the Shanghai Stock Exchange.
  • E. SSE 50 Index
    The SSE 50 Index is a blue-chip stock market index that tracks the performance of 50 of the largest and most liquid companies listed on the Shanghai Stock Exchange.
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a2d01f9c8190849f252f22519550 completed April 10, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82ce2904819094cf5be87fb14fca completed April 27, 2026, 3:37 p.m.
Created at: April 8, 2026, 9:39 p.m.