Triple

T31309695

Position	Surface form	Disambiguated ID	Type / Status
Subject	وزارة الخارجية والمغتربين (لبنان)	`E798428`	entity
Predicate	تابعة_إلى	`P159219`	FINISHED
Object	مجلس الوزراء اللبناني مجلس الوزراء اللبناني هو السلطة التنفيذية الأساسية في لبنان، يضم رئيس الحكومة والوزراء ويتولى وضع السياسات العامة وإدارة شؤون الدولة.	`E1956742`	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: مجلس الوزراء اللبناني | Statement: [وزارة الخارجية والمغتربين (لبنان), تابعة_إلى, مجلس الوزراء اللبناني]

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: مجلس الوزراء اللبناني
Triple: [وزارة الخارجية والمغتربين (لبنان), تابعة_إلى, مجلس الوزراء اللبناني]

Generated description

مجلس الوزراء اللبناني هو السلطة التنفيذية الأساسية في لبنان، يضم رئيس الحكومة والوزراء ويتولى وضع السياسات العامة وإدارة شؤون الدولة.

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

Target predicate: تابعة_إلى
Context triple: [وزارة الخارجية والمغتربين (لبنان), تابعة_إلى, مجلس الوزراء اللبناني]

A. follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
B. eraFollowed
Indicates that one historical era comes directly after another in chronological sequence.
C. followsTo
Indicates that one entity moves or proceeds behind another entity toward a specific destination or target.
D. يتبعها chosen
Indicates that one entity comes after, succeeds, or is subordinate to another in order, sequence, or hierarchy.
E. followedIn
Indicates that one entity began following or subscribing to another entity, typically in a social or sequential context.
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_69f224e1932c81908fef14f7b03a10b7`	completed	April 29, 2026, 3:33 p.m.
NER	Named-entity recognition	`batch_69f69edbb7648190bd89c57e0932eac1`	completed	May 3, 2026, 1:03 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2a1e40360c8190a76720d82b86892a`	completed	June 11, 2026, 2:32 a.m.
NEDg	Description generation	`batch_6a2a37c4113081908e84ae01d95befea`	completed	June 11, 2026, 4:21 a.m.
NED2	Entity disambiguation (via description)	`batch_6a2a382a072c8190a8a94bd48ab0bdaf`	completed	June 11, 2026, 4:23 a.m.
PD	Predicate disambiguation	`batch_69f69d1bf8cc8190a78dfa5ab00daf3a`	completed	May 3, 2026, 12:55 a.m.

Created at: April 29, 2026, 9:15 p.m.