Triple

T17314299
Position Surface form Disambiguated ID Type / Status
Subject Hoek van Holland Haven E420380 entity
Predicate hasStationCode P1289 FINISHED
Object Hld
Hld is the official station code for Hoek van Holland Haven railway station in the Netherlands.
E1261988 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: Hld | Statement: [Hoek van Holland Haven, hasStationCode, Hld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hld
Context triple: [Hoek van Holland Haven, hasStationCode, Hld]
  • A. HOL
    HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
  • B. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • C. H-D
    H-D is the commonly used abbreviation for Harley-Davidson, the iconic American motorcycle manufacturer known for heavyweight cruiser bikes and a strong biker subculture.
  • D. HLU
    HLU is the National Rail station code for Helensburgh Upper railway station in Argyll and Bute, Scotland.
  • E. Hadl
    Hadl is the surname of John Hadl, a notable American football quarterback who played primarily for the San Diego Chargers in the AFL and NFL.
  • 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: Hld
Triple: [Hoek van Holland Haven, hasStationCode, Hld]
Generated description
Hld is the official station code for Hoek van Holland Haven railway station in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hld
Target entity description: Hld is the official station code for Hoek van Holland Haven railway station in the Netherlands.
  • A. HOL
    HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
  • B. HL
    HL is the vehicle registration code used on license plates for the German city of Lübeck.
  • C. H-D
    H-D is the commonly used abbreviation for Harley-Davidson, the iconic American motorcycle manufacturer known for heavyweight cruiser bikes and a strong biker subculture.
  • D. HLU
    HLU is the National Rail station code for Helensburgh Upper railway station in Argyll and Bute, Scotland.
  • E. Hadl
    Hadl is the surname of John Hadl, a notable American football quarterback who played primarily for the San Diego Chargers in the AFL and NFL.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4399b4dcc8190996d79d04ba88795 completed April 19, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180e6e830819097b33d6b99232727 completed May 11, 2026, 7:10 a.m.
NEDg Description generation batch_6a01853590d081908f6523c55e4f610d completed May 11, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a01860e39788190bbf5ca5188352d95 completed May 11, 2026, 7:32 a.m.
Created at: April 10, 2026, 5:43 a.m.