Triple

T38279997
Position Surface form Disambiguated ID Type / Status
Subject Ar-Rabitah al-Qalamiyah E1022056 entity
Predicate hasNotableMember P304 FINISHED
Object Najeeb Armanious
Najeeb Armanious was a writer associated with the early 20th-century Arab-American literary movement centered around the Ar-Rabitah al-Qalamiyah (Pen League).
E2266128 NE FINISHED

How this triple was built (2 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: Najeeb Armanious | Statement: [Ar-Rabitah al-Qalamiyah, hasNotableMember, Najeeb Armanious]
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: Najeeb Armanious
Triple: [Ar-Rabitah al-Qalamiyah, hasNotableMember, Najeeb Armanious]
Generated description
Najeeb Armanious was a writer associated with the early 20th-century Arab-American literary movement centered around the Ar-Rabitah al-Qalamiyah (Pen League).

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_69f76df0cddc81908d16c1556ff4097f completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcc5930f4081909a99e6ddc8766f88 completed May 7, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41a7dbe4b081908a61c637ab370906 completed June 28, 2026, 11:01 p.m.
NEDg Description generation batch_6a41a925216c8190a1aa0ae05d80a4aa completed June 28, 2026, 11:07 p.m.
NED2 Entity disambiguation (via description) batch_6a41a9f0b9748190a604e440751cbf67 completed June 28, 2026, 11:10 p.m.
Created at: May 3, 2026, 4:30 p.m.