Triple

T27068757

Position	Surface form	Disambiguated ID	Type / Status
Subject	Port-de-Paix	`E685253`	entity
Predicate	arrondissementCapitalOf	`P115205`	FINISHED
Object	Port-de-Paix Arrondissement Port-de-Paix Arrondissement is an administrative division in Haiti’s Nord-Ouest department that includes the coastal city of Port-de-Paix and its surrounding communes.	`E1755381`	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: Port-de-Paix Arrondissement | Statement: [Port-de-Paix, arrondissementCapitalOf, Port-de-Paix Arrondissement]

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-de-Paix Arrondissement
Triple: [Port-de-Paix, arrondissementCapitalOf, Port-de-Paix Arrondissement]

Generated description

Port-de-Paix Arrondissement is an administrative division in Haiti’s Nord-Ouest department that includes the coastal city of Port-de-Paix and its surrounding communes.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: arrondissementCapitalOf
Context triple: [Port-de-Paix, arrondissementCapitalOf, Port-de-Paix Arrondissement]

A. capitalOfArrondissement chosen
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
B. countryCapitalArrondissement
Indicates that a given arrondissement is an administrative district within the capital city of a specified country.
C. capitalOfCommune
Indicates that one place serves as the administrative capital or chief town of a given commune.
D. hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
E. hasNumberOfArrondissements
Indicates the relationship that specifies how many arrondissements (administrative districts) are associated with a given entity.
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_69ef14835fcc81908bd737b4267ae528`	completed	April 27, 2026, 7:47 a.m.
NER	Named-entity recognition	`batch_69f622eb05c08190af8651dda80ace28`	completed	May 2, 2026, 4:14 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a123ad803688190bb579cd9339576bb`	completed	May 23, 2026, 11:40 p.m.
NEDg	Description generation	`batch_6a123c27062881908664273fcb5ea8b8`	completed	May 23, 2026, 11:45 p.m.
NED2	Entity disambiguation (via description)	`batch_6a123cea536c81908bfb43ef2224a964`	completed	May 23, 2026, 11:48 p.m.
PD	Predicate disambiguation	`batch_69f61b3ee7b08190a0a1bc5d26b757aa`	completed	May 2, 2026, 3:41 p.m.

Created at: April 27, 2026, 8:26 a.m.