Triple

T24651931
Position Surface form Disambiguated ID Type / Status
Subject ISO 3166-2:HT E610271 entity
Predicate subdivisionNameExample P157663 FINISHED
Object Nord-Ouest
Nord-Ouest is a department in northwestern Haiti known for its coastal location along the Caribbean Sea and its capital city, Port-de-Paix.
 E1646109 NE FINISHED

How this triple was built (3 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: Nord-Ouest | Statement: [ISO 3166-2:HT, subdivisionNameExample, Nord-Ouest]
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: Nord-Ouest
Triple: [ISO 3166-2:HT, subdivisionNameExample, Nord-Ouest]
Generated description
Nord-Ouest is a department in northwestern Haiti known for its coastal location along the Caribbean Sea and its capital city, Port-de-Paix.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: subdivisionNameExample
Context triple: [ISO 3166-2:HT, subdivisionNameExample, Nord-Ouest]
  • A. subdivisionNameExample chosen
    Indicates that the predicate provides an example name of a subdivision (such as a district, region, or administrative area) associated with an entity.
  • B. subdivisionNameType
    Indicates the type or category of a named geographic or administrative subdivision (e.g., province, state, district) associated with an entity.
  • C. subdivisionName0
    Indicates the name assigned to the first (primary) subdivision or sub-unit associated with an entity.
  • D. subdivisionName1
    Indicates that the first named subdivision is identified by a specific name or designation within a larger geographic or organizational hierarchy.
  • E. subdivisionNameLocal
    Indicates the locally used or native-language name assigned to a specific administrative or geographic subdivision.
  • F. None of above.

Provenance (6 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_69e2c4d350a481909170482bc2ce6af9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f47b865df48190bf4b6d3e9f9305e6 completed May 1, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a100ff4a6e88190ba64dcbb04ed4246 completed May 22, 2026, 8:12 a.m.
NEDg Description generation batch_6a1010a696e48190a2f055d2a9e35eb7 completed May 22, 2026, 8:15 a.m.
NED2 Entity disambiguation (via description) batch_6a10137faa288190ba9e17f59e14d4d3 completed May 22, 2026, 8:27 a.m.
PD Predicate disambiguation batch_69f4682c8a3c8190adbfaac99474eaaf completed May 1, 2026, 8:45 a.m.
Created at: April 18, 2026, 2:34 a.m.