Triple

T9106440
Position Surface form Disambiguated ID Type / Status
Subject Sinopec E218488 entity
Predicate competitor P1375 FINISHED
Object PetroChina E222489 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: PetroChina | Statement: [Sinopec, competitor, PetroChina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PetroChina
Context triple: [Sinopec, competitor, PetroChina]
  • A. PetroChina chosen
    PetroChina is one of China’s largest state-owned oil and gas companies, engaged in exploration, production, refining, and marketing of petroleum and petrochemical products.
  • B. Sinopec
    Sinopec is one of China’s largest state-owned oil and petrochemical companies, engaged in exploration, refining, and marketing of petroleum and chemical products worldwide.
  • C. Shengli Oilfield
    Shengli Oilfield is one of China’s largest and most productive oil fields, located in Shandong Province and operated primarily by Sinopec.
  • D. CITIC Group
    CITIC Group is a large state-owned Chinese conglomerate headquartered in Beijing, with major interests in finance, real estate, resources, and infrastructure.
  • E. China State Construction Engineering Corporation
    China State Construction Engineering Corporation is one of the world’s largest construction and engineering companies, responsible for major infrastructure and skyscraper projects in China and abroad.
  • 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_69ca83db7448819090d0a5de842ef2ac completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca57286a88190b256d2461c5c0aed completed April 1, 2026, 4:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0302bfa00819097e752f1d0581d2d completed April 3, 2026, 9:25 p.m.
Created at: March 30, 2026, 7:16 p.m.