Triple

T4284015
Position Surface form Disambiguated ID Type / Status
Subject Port of Rotterdam E97221 entity
Predicate hasFacility P105 FINISHED
Object Eemhaven
Eemhaven is a major container and short-sea shipping terminal area within the Port of Rotterdam in the Netherlands.
E428010 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: Eemhaven | Statement: [Port of Rotterdam, hasFacility, Eemhaven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eemhaven
Context triple: [Port of Rotterdam, hasFacility, Eemhaven]
  • A. Eemshaven
    Eemshaven is a major seaport and energy hub in the north of the Netherlands, known for its power plants, data centers, and offshore wind connections.
  • B. Diemen
    Diemen is a town and municipality in the province of North Holland in the Netherlands, located just southeast of Amsterdam.
  • C. Hoendiep
    Hoendiep is a canal in the Dutch province of Groningen that serves as an important regional waterway and transport route.
  • D. Alblasserdam
    Alblasserdam is a town and municipality in the western Netherlands, situated along the Noord River and known for its proximity to the Kinderdijk windmills.
  • E. Monnickendam
    Monnickendam is a historic fishing town in North Holland, Netherlands, known for its well-preserved old harbor and traditional Dutch architecture.
  • 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: Eemhaven
Triple: [Port of Rotterdam, hasFacility, Eemhaven]
Generated description
Eemhaven is a major container and short-sea shipping terminal area within the Port of Rotterdam in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eemhaven
Target entity description: Eemhaven is a major container and short-sea shipping terminal area within the Port of Rotterdam in the Netherlands.
  • A. Eemshaven
    Eemshaven is a major seaport and energy hub in the north of the Netherlands, known for its power plants, data centers, and offshore wind connections.
  • B. Diemen
    Diemen is a town and municipality in the province of North Holland in the Netherlands, located just southeast of Amsterdam.
  • C. Hoendiep
    Hoendiep is a canal in the Dutch province of Groningen that serves as an important regional waterway and transport route.
  • D. Alblasserdam
    Alblasserdam is a town and municipality in the western Netherlands, situated along the Noord River and known for its proximity to the Kinderdijk windmills.
  • E. Monnickendam
    Monnickendam is a historic fishing town in North Holland, Netherlands, known for its well-preserved old harbor and traditional Dutch architecture.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3503c062c81908f9a9eeab5381ec9 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c72804ac81908f8d2c111276b6b7 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7ab41fc81909813233bd729e989 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c81d6e188190a1f0f21a990943d0 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:07 p.m.