Triple

T37389778
Position Surface form Disambiguated ID Type / Status
Subject André P. Brink E928671 entity
Predicate awardReceived P11 FINISHED
Object Martin Luther King Memorial Prize
The Martin Luther King Memorial Prize is a literary award recognizing works that promote civil rights, social justice, and racial equality in the spirit of Martin Luther King Jr.
E2224791 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: Martin Luther King Memorial Prize | Statement: [André P. Brink, awardReceived, Martin Luther King Memorial Prize]
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: Martin Luther King Memorial Prize
Triple: [André P. Brink, awardReceived, Martin Luther King Memorial Prize]
Generated description
The Martin Luther King Memorial Prize is a literary award recognizing works that promote civil rights, social justice, and racial equality in the spirit of Martin Luther King Jr.

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_69f76ebb10c481909b54b9dba263e29f completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8d38095c8190bcd71b32cb306572 completed May 6, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40770166248190996f7595806b2489 completed June 28, 2026, 1:21 a.m.
NEDg Description generation batch_6a40777f8658819086f67175409b28fa completed June 28, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_6a407806efbc81909b322cc504066e01 completed June 28, 2026, 1:25 a.m.
Created at: May 3, 2026, 4:16 p.m.