Triple

T25110502

Position	Surface form	Disambiguated ID	Type / Status
Subject	محمد علی جناح	`E628975`	entity
Predicate	جائے_تعلیم	`P335`	FINISHED
Object	لنکنز اِن لنکنز اِن لندن کا ایک تاریخی اور معزز ادارۂ قانون ہے جو بیرسٹرز کی تربیت اور قانونی پیشہ ور افراد کی رکنیت کے لیے مشہور ہے۔	`E1662200`	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: لنکنز اِن | Statement: [محمد علی جناح, جائے_تعلیم, لنکنز اِن]

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: لنکنز اِن
Triple: [محمد علی جناح, جائے_تعلیم, لنکنز اِن]

Generated description

لنکنز اِن لندن کا ایک تاریخی اور معزز ادارۂ قانون ہے جو بیرسٹرز کی تربیت اور قانونی پیشہ ور افراد کی رکنیت کے لیے مشہور ہے۔

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

Target predicate: جائے_تعلیم
Context triple: [محمد علی جناح, جائے_تعلیم, لنکنز اِن]

A. освіта
Indicates that one entity provides, has, or is associated with the education or educational background of another entity.
B. educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
C. educationAndCulture
Indicates a relationship where activities, policies, or influences connect educational processes with cultural development, preservation, or expression.
D. educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
E. educates chosen
Indicates that one entity provides instruction, knowledge, or training to another 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_69e2ff3169d08190973b6061d5009abd`	completed	April 18, 2026, 3:49 a.m.
NER	Named-entity recognition	`batch_69f465767c48819086fa0573dca12276`	completed	May 1, 2026, 8:33 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a1048f4cf108190b1bc1ccc3f7829bd`	completed	May 22, 2026, 12:15 p.m.
NEDg	Description generation	`batch_6a104a09687c819088fa6a920817bbb7`	completed	May 22, 2026, 12:20 p.m.
NED2	Entity disambiguation (via description)	`batch_6a104aa15f248190ba69524b7d516bc1`	completed	May 22, 2026, 12:22 p.m.
PD	Predicate disambiguation	`batch_69f45cfb53f4819099bba48c5057e787`	completed	May 1, 2026, 7:57 a.m.

Created at: April 18, 2026, 6:26 a.m.