Triple

T7934207
Position Surface form Disambiguated ID Type / Status
Subject OpenID Connect E184249 entity
Predicate uses P98 FINISHED
Object HTTPS E7608 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: HTTPS | Statement: [OpenID Connect, uses, HTTPS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HTTPS
Context triple: [OpenID Connect, uses, HTTPS]
  • A. HTTPS chosen
    HTTPS is the secure version of the HTTP protocol that encrypts data exchanged between a client and server to protect confidentiality and integrity on the web.
  • B. SSL
    SSL (Secure Sockets Layer) is a cryptographic protocol designed to provide secure, encrypted communication over a computer network, commonly used to protect data transmitted between clients and servers.
  • C. HTTPS Everywhere
    HTTPS Everywhere is a browser extension that automatically enforces secure, encrypted HTTPS connections to websites to protect users’ privacy and security online.
  • D. TLS
    TLS is the IATA airport code for Toulouse-Blagnac Airport, the main international airport serving Toulouse in southwestern France.
  • E. TLS
    TLS (Transport Layer Security) is a cryptographic protocol that secures data transmitted over networks by providing encryption, authentication, and integrity between communicating applications.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aeb132c8190bea4906aaf51b869 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe019a094819082baecdcb007c84f completed March 31, 2026, 2:54 p.m.
Created at: March 30, 2026, 5:08 p.m.