Triple

T1427046
Position Surface form Disambiguated ID Type / Status
Subject Walvis Bay E30355 entity
Predicate nearbyCity P350 FINISHED
Object Swakopmund
Swakopmund is a coastal city in Namibia known for its German colonial architecture, cool Atlantic climate, and popularity as a tourist destination and adventure-sports hub.
E171457 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: Swakopmund | Statement: [Walvis Bay, nearbyCity, Swakopmund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swakopmund
Context triple: [Walvis Bay, nearbyCity, Swakopmund]
  • A. Lüderitz
    Lüderitz is a coastal town in southwestern Namibia known for its Atlantic shoreline, nearby desert landscapes, and rich marine ecosystem influenced by the Benguela Current.
  • B. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • C. Oudenhoorn
    Oudenhoorn is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Ovambo
    Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
  • 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: Swakopmund
Triple: [Walvis Bay, nearbyCity, Swakopmund]
Generated description
Swakopmund is a coastal city in Namibia known for its German colonial architecture, cool Atlantic climate, and popularity as a tourist destination and adventure-sports hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Swakopmund
Target entity description: Swakopmund is a coastal city in Namibia known for its German colonial architecture, cool Atlantic climate, and popularity as a tourist destination and adventure-sports hub.
  • A. Lüderitz
    Lüderitz is a coastal town in southwestern Namibia known for its Atlantic shoreline, nearby desert landscapes, and rich marine ecosystem influenced by the Benguela Current.
  • B. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • C. Oudenhoorn
    Oudenhoorn is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Ovambo
    Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4bfc79481908d370ec839ddbd9f completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c9999b0819086573fb974952f63 completed March 8, 2026, 6:52 a.m.
NEDg Description generation batch_69ad1f2071708190931a1f3cd35002d6 completed March 8, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69ad2141e5f48190a34021b7b3c2a252 completed March 8, 2026, 7:12 a.m.
Created at: March 1, 2026, 8 p.m.