Triple

T27292056
Position Surface form Disambiguated ID Type / Status
Subject Amha Selassie I E688654 entity
Predicate child P120 FINISHED
Object Zera Yacob Amha Selassie
Zera Yacob Amha Selassie is the grandson of Emperor Haile Selassie and the current claimant to the Ethiopian imperial throne.
 E1787688 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: Zera Yacob Amha Selassie | Statement: [Amha Selassie I, child, Zera Yacob Amha Selassie]
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: Zera Yacob Amha Selassie
Triple: [Amha Selassie I, child, Zera Yacob Amha Selassie]
Generated description
Zera Yacob Amha Selassie is the grandson of Emperor Haile Selassie and the current claimant to the Ethiopian imperial throne.

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_69ef355a96308190a2bed991525fb278 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62759cb288190904e0b0531fea34d completed May 2, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e4339b8c8190a4a8898f14807e67 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e4bc42e081909864bb2839e08143 completed May 24, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a12e551ec288190b818e25bf2e62f45 completed May 24, 2026, 11:47 a.m.
Created at: April 27, 2026, 11:16 a.m.