Triple

T6911511
Position Surface form Disambiguated ID Type / Status
Subject Swiss Re E159943 entity
Predicate tickerSymbol P1447 FINISHED
Object SREN
SREN is the stock ticker symbol for Swiss Re, one of the world’s largest reinsurance companies headquartered in Zurich, Switzerland.
 E627752 NE FINISHED

How this triple was built (4 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: SREN | Statement: [Swiss Re, tickerSymbol, SREN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SREN
Context triple: [Swiss Re, tickerSymbol, SREN]
  • A. saronen
    Saronen is a traditional wind instrument central to the folk music of the Madurese people of Indonesia.
  • B. saron
    The saron is a key metallophone instrument in Javanese and Balinese gamelan ensembles, featuring bronze bars struck with a mallet to produce the core melodic line.
  • C. SERNANP
    SERNANP is Peru’s national authority responsible for managing and conserving the country’s system of protected natural areas.
  • D. SRES
    SRES is the School of Resources and Environmental Science at Wuhan University, a faculty focused on education and research in natural resources, geography, and environmental science.
  • E. SEREB
    SEREB was a French aerospace company involved in the development of ballistic missiles and space launch vehicles before being merged into Aérospatiale.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SREN
Triple: [Swiss Re, tickerSymbol, SREN]
Generated description
SREN is the stock ticker symbol for Swiss Re, one of the world’s largest reinsurance companies headquartered in Zurich, Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SREN
Target entity description: SREN is the stock ticker symbol for Swiss Re, one of the world’s largest reinsurance companies headquartered in Zurich, Switzerland.
  • A. saronen
    Saronen is a traditional wind instrument central to the folk music of the Madurese people of Indonesia.
  • B. saron
    The saron is a key metallophone instrument in Javanese and Balinese gamelan ensembles, featuring bronze bars struck with a mallet to produce the core melodic line.
  • C. SERNANP
    SERNANP is Peru’s national authority responsible for managing and conserving the country’s system of protected natural areas.
  • D. SRES
    SRES is the School of Resources and Environmental Science at Wuhan University, a faculty focused on education and research in natural resources, geography, and environmental science.
  • E. SEREB
    SEREB was a French aerospace company involved in the development of ballistic missiles and space launch vehicles before being merged into Aérospatiale.
  • F. None of above. chosen

Provenance (5 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_69c68839ccb88190b4aa5cc1aca3448f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9c135b48190b332aedf1d52bdb7 completed March 27, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7490c95548190a493d3fd23d1d7a5 completed March 28, 2026, 3:20 a.m.
NEDg Description generation batch_69c749d4b088819095f991f976592d04 completed March 28, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_69c74aab12988190bd23cfcc06c55cde completed March 28, 2026, 3:27 a.m.
Created at: March 27, 2026, 2:25 p.m.