Triple

T4848662
Position Surface form Disambiguated ID Type / Status
Subject 高錕 E108355 entity
Predicate employer P7 FINISHED
Object ITT公司 E108357 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: ITT公司 | Statement: [高錕, employer, ITT公司]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ITT公司
Context triple: [高錕, employer, ITT公司]
  • A. ITT Corporation chosen
    ITT Corporation is a diversified American manufacturing and engineering company historically known for its involvement in telecommunications, defense, and industrial products.
  • B. Lucent Technologies
    Lucent Technologies was a major American telecommunications equipment company, spun off from AT&T, known for its Bell Labs research arm and contributions to networking and communications technology.
  • C. Telcordia Technologies
    Telcordia Technologies is a telecommunications research and development company known for creating industry standards and software solutions for network planning, management, and operations.
  • D. IBM
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • E. Tokyo Tsushin Kogyo
    Tokyo Tsushin Kogyo was the original name of the Japanese electronics company that later became globally known as Sony.
  • 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_69bd4409b264819085ab855f3eb5381a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d1c5594819094fe021d7717032d completed March 20, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cdafb3481908594ae883c6e9872 completed March 21, 2026, 8:54 a.m.
Created at: March 20, 2026, 1:25 p.m.