Triple

T1155307
Position Surface form Disambiguated ID Type / Status
Subject Ray Tomlinson E23769 entity
Predicate employer P7 FINISHED
Object BBN Technologies E96778 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: BBN Technologies | Statement: [Ray Tomlinson, employer, BBN Technologies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BBN Technologies
Context triple: [Ray Tomlinson, employer, BBN Technologies]
  • A. BBN Technologies chosen
    BBN Technologies is an American research and development company renowned for its pioneering work in computer networking and its key role in creating the ARPANET, the precursor to the modern internet.
  • B. BBN
    BBN is the early-universe process that produced the lightest elements—mainly hydrogen, helium, and small amounts of lithium—within the first few minutes after the Big Bang.
  • 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. 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.
  • E. Agere Systems
    Agere Systems was a semiconductor company specializing in communications and networking integrated circuits, formed as a spin-off from Lucent Technologies.
  • 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_69a493f0d32c8190ac74bad3c87f2641 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc912300819084c9c69783055a70 completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5eb81790819087016b1620353417 completed March 7, 2026, 5:22 p.m.
Created at: March 1, 2026, 7:44 p.m.