Triple

T36375817
Position Surface form Disambiguated ID Type / Status
Subject Ala ad-Din Tekish E895894 entity
Predicate recognizedBy P653 FINISHED
Object Abbasid Caliph al-Nasir
Abbasid Caliph al-Nasir was a 12th–13th century Abbasid ruler in Baghdad known for attempting to restore caliphal political authority and influence across the Islamic world.
E2179770 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: Abbasid Caliph al-Nasir | Statement: [Ala ad-Din Tekish, recognizedBy, Abbasid Caliph al-Nasir]
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: Abbasid Caliph al-Nasir
Triple: [Ala ad-Din Tekish, recognizedBy, Abbasid Caliph al-Nasir]
Generated description
Abbasid Caliph al-Nasir was a 12th–13th century Abbasid ruler in Baghdad known for attempting to restore caliphal political authority and influence across the Islamic world.

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_69f76e5115588190ad8738860b7bc68b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bb17487c819084b51886a1a1c456 completed May 3, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a33ed66c8190b8655bf9a38cb082 completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a5173f648190b3b4397d6913e424 completed June 22, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a39a659978c8190bbdf4e8057585bf5 completed June 22, 2026, 9:17 p.m.
Created at: May 3, 2026, 4:10 p.m.