Triple

T3925358
Position Surface form Disambiguated ID Type / Status
Subject Areva E93261 entity
Predicate tickerSymbol P1447 FINISHED
Object AREVA E93261 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: AREVA | Statement: [Areva, tickerSymbol, AREVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AREVA
Context triple: [Areva, tickerSymbol, AREVA]
  • A. Areva chosen
    Areva was a French multinational group specializing in nuclear power and renewable energy technologies, known for its involvement in the entire nuclear fuel cycle.
  • B. Électricité de France
    Électricité de France is France’s state-owned electric utility company and one of the world’s largest producers and distributors of electricity, particularly known for its extensive nuclear power fleet.
  • C. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • D. Siemens Energy
    Siemens Energy is a global energy technology company specializing in power generation, transmission, and related services for conventional and renewable energy systems.
  • E. GDF Suez
    GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeed7f3cc881909464db1970ba39ae completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53387775881909479f4e1fcecdaca completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:23 p.m.