Triple

T491696
Position Surface form Disambiguated ID Type / Status
Subject Dag Hammarskjöld Library E10203 entity
Predicate abbreviation P43 FINISHED
Object DHL E10203 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: DHL | Statement: [Dag Hammarskjöld Library, abbreviation, DHL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DHL
Context triple: [Dag Hammarskjöld Library, abbreviation, DHL]
  • A. DHL chosen
    DHL is the Dag Hammarskjöld Library, the United Nations’ main research and information resource center located at its headquarters in New York.
  • B. FedEx
    FedEx is a global courier delivery services company known for its overnight shipping and pioneering real-time package tracking.
  • C. United Parcel Service (UPS)
    United Parcel Service (UPS) is a global package delivery and supply chain management company known for its extensive logistics network and brown delivery trucks.
  • D. Channel Express
    Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
  • E. HK Express
    HK Express is a Hong Kong-based low-cost airline operating regional flights across Asia.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f0f959b481908f9f28fb96695924 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4778034fc8190bedcc537fed5cef9 completed March 1, 2026, 5:29 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.