Triple

T3932213
Position Surface form Disambiguated ID Type / Status
Subject Port of Casablanca E90819 entity
Predicate hasUNLocode P1492 FINISHED
Object MACAS
MACAS is the UN/LOCODE identifier assigned to the Port of Casablanca in Morocco for international trade and transport logistics.
 E399576 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: MACAS | Statement: [Port of Casablanca, hasUNLocode, MACAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MACAS
Context triple: [Port of Casablanca, hasUNLocode, MACAS]
  • A. MACP
    MACP is a professional designation signifying Mastership in the American College of Physicians, awarded to internists for outstanding achievement and contributions to medicine.
  • B. MAMAC
    MAMAC is a modern and contemporary art museum in Nice, France, known for its collections of postwar European and American art.
  • C. MCA
    MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
  • D. MCA
    MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
  • E. MCA
    MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
  • 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: MACAS
Triple: [Port of Casablanca, hasUNLocode, MACAS]
Generated description
MACAS is the UN/LOCODE identifier assigned to the Port of Casablanca in Morocco for international trade and transport logistics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MACAS
Target entity description: MACAS is the UN/LOCODE identifier assigned to the Port of Casablanca in Morocco for international trade and transport logistics.
  • A. MACP
    MACP is a professional designation signifying Mastership in the American College of Physicians, awarded to internists for outstanding achievement and contributions to medicine.
  • B. MAMAC
    MAMAC is a modern and contemporary art museum in Nice, France, known for its collections of postwar European and American art.
  • C. MCA
    MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
  • D. MCA
    MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
  • E. MCA
    MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedaaf3c881909539831bf3a8bf10 completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52887d4a48190b51df3f51ff197c0 completed March 14, 2026, 9:21 a.m.
NEDg Description generation batch_69b529a1486881908ff348558199232b completed March 14, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69b52a43c6f081908366d9848728f98a completed March 14, 2026, 9:28 a.m.
Created at: March 9, 2026, 3:23 p.m.