Triple

T6901779
Position Surface form Disambiguated ID Type / Status
Subject Northern Haiti E159511 entity
Predicate contains P35 FINISHED
Object Port-Margot
Port-Margot is a coastal commune in northern Haiti known for its rural communities, agriculture, and proximity to the Caribbean Sea.
 E627223 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: Port-Margot | Statement: [Northern Haiti, contains, Port-Margot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Port-Margot
Context triple: [Northern Haiti, contains, Port-Margot]
  • A. Saint-Marc
    Saint-Marc is a coastal city in western Haiti that serves as an important commercial and maritime hub on the Gulf of Gonâve.
  • B. Cité
    Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
  • C. Ville-la-Grand
    Ville-la-Grand is a commune in the Haute-Savoie department of southeastern France, situated near the Swiss border in the urban area of Annemasse.
  • D. Crevel
    Crevel is a vain, wealthy former perfumer and libertine in Honoré de Balzac’s novel "La Cousine Bette," emblematic of the corrupt bourgeois society he satirizes.
  • E. Papelotte
    Papelotte is a farmhouse and hamlet in Belgium that served as a key defensive position on the Allied left flank during the Battle of Waterloo in 1815.
  • 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: Port-Margot
Triple: [Northern Haiti, contains, Port-Margot]
Generated description
Port-Margot is a coastal commune in northern Haiti known for its rural communities, agriculture, and proximity to the Caribbean Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Port-Margot
Target entity description: Port-Margot is a coastal commune in northern Haiti known for its rural communities, agriculture, and proximity to the Caribbean Sea.
  • A. Saint-Marc
    Saint-Marc is a coastal city in western Haiti that serves as an important commercial and maritime hub on the Gulf of Gonâve.
  • B. Cité
    Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
  • C. Ville-la-Grand
    Ville-la-Grand is a commune in the Haute-Savoie department of southeastern France, situated near the Swiss border in the urban area of Annemasse.
  • D. Crevel
    Crevel is a vain, wealthy former perfumer and libertine in Honoré de Balzac’s novel "La Cousine Bette," emblematic of the corrupt bourgeois society he satirizes.
  • E. Papelotte
    Papelotte is a farmhouse and hamlet in Belgium that served as a key defensive position on the Allied left flank during the Battle of Waterloo in 1815.
  • 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_69c6883822e0819091e321526f20ae0a completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d98749208190842ac075255ca249 completed March 27, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748f0dc448190914e38d780644698 completed March 28, 2026, 3:20 a.m.
NEDg Description generation batch_69c749f7ab5c8190ab823fac27f7484d completed March 28, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_69c74a6f828c8190bf0cc56227b1a5b2 completed March 28, 2026, 3:26 a.m.
Created at: March 27, 2026, 2:24 p.m.