Triple

T8643178
Position Surface form Disambiguated ID Type / Status
Subject HSSS E204704 entity
Predicate icaoCode P419 FINISHED
Object HSSS E204704 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: HSSS | Statement: [HSSS, icaoCode, HSSS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HSSS
Context triple: [HSSS, icaoCode, HSSS]
  • A. HSSS chosen
    HSSS is the ICAO airport code for Khartoum International Airport, the main international gateway to Sudan’s capital city.
  • B. HSS
    HSS is the abbreviation for the Holly Springs Salamanders, a collegiate summer baseball team based in Holly Springs, North Carolina.
  • C. HSS
    HSS (Home Subscriber Server) is a core network database in IP Multimedia Subsystem (IMS) architectures that manages user identities, subscription profiles, and authentication for telecom services.
  • D. SSS
    SSS is the commonly used abbreviation for the Selective Service System, the U.S. government agency that maintains information on individuals potentially subject to military conscription.
  • E. WSSS
    WSSS is the ICAO airport code for Singapore Changi Airport, one of the world’s busiest and most highly rated international air hubs.
  • 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_69ca834ca1c88190a11ffb0200342fac completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc479720f481908ee2b12c2775e76a completed March 31, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebc42922c819099a464d2e347dec4 completed April 2, 2026, 6:58 p.m.
Created at: March 30, 2026, 6:28 p.m.