Triple

T4824902
Position Surface form Disambiguated ID Type / Status
Subject Namur E107798 entity
Predicate hasUNLOCODE P1492 FINISHED
Object BENAM
BENAM is the UN/LOCODE designation used in international trade and transport to identify the city of Namur in Belgium.
 E473360 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: BENAM | Statement: [Namur, hasUNLOCODE, BENAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BENAM
Context triple: [Namur, hasUNLOCODE, BENAM]
  • A. BEN
    BEN is the three-letter IATA airport code assigned to Benina International Airport serving Benghazi, Libya.
  • B. Bamanankan
    Bamanankan is a Mande language widely spoken in Mali and neighboring West African countries, particularly by the Bambara people.
  • C. Beng
    Beng is the ISO 15924 four-letter code that designates the Bengali script used for writing the Bengali language and several other languages of the Indian subcontinent.
  • D. Beenieman
    Beenieman is a prominent Jamaican dancehall deejay and reggae artist often referred to as the "King of Dancehall."
  • E. Beng ü Bade
    Beng ü Bade is a celebrated allegorical poem by the 16th-century Azerbaijani poet Fuzuli, known for its rich mystical and philosophical themes.
  • 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: BENAM
Triple: [Namur, hasUNLOCODE, BENAM]
Generated description
BENAM is the UN/LOCODE designation used in international trade and transport to identify the city of Namur in Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BENAM
Target entity description: BENAM is the UN/LOCODE designation used in international trade and transport to identify the city of Namur in Belgium.
  • A. BEN
    BEN is the three-letter IATA airport code assigned to Benina International Airport serving Benghazi, Libya.
  • B. Bamanankan
    Bamanankan is a Mande language widely spoken in Mali and neighboring West African countries, particularly by the Bambara people.
  • C. Beng
    Beng is the ISO 15924 four-letter code that designates the Bengali script used for writing the Bengali language and several other languages of the Indian subcontinent.
  • D. Beenieman
    Beenieman is a prominent Jamaican dancehall deejay and reggae artist often referred to as the "King of Dancehall."
  • E. Beng ü Bade
    Beng ü Bade is a celebrated allegorical poem by the 16th-century Azerbaijani poet Fuzuli, known for its rich mystical and philosophical themes.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cadb2bc81909455149e46eb593a completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4dca2b708190ac05c91ba04d9ff6 completed March 21, 2026, 7:50 a.m.
NEDg Description generation batch_69be4fc6ea3c819099ede84700eb5a5a completed March 21, 2026, 7:59 a.m.
NED2 Entity disambiguation (via description) batch_69be5146f1ac8190977512323af69487 completed March 21, 2026, 8:05 a.m.
Created at: March 20, 2026, 1:24 p.m.