Triple

T37243682
Position Surface form Disambiguated ID Type / Status
Subject Ibtihaj Muhammad E923783 entity
Predicate wrote P2831 FINISHED
Object children's book "The Proudest Blue"
"The Proudest Blue" is a children's picture book that celebrates a young Muslim girl's pride in wearing her hijab, highlighting themes of identity, family, and resilience in the face of bullying.
E2219053 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: children's book "The Proudest Blue" | Statement: [Ibtihaj Muhammad, wrote, children's book "The Proudest Blue"]
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: children's book "The Proudest Blue"
Triple: [Ibtihaj Muhammad, wrote, children's book "The Proudest Blue"]
Generated description
"The Proudest Blue" is a children's picture book that celebrates a young Muslim girl's pride in wearing her hijab, highlighting themes of identity, family, and resilience in the face of bullying.

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_69f76ea9fee88190a589f661d95a7189 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb36fa229481908fcc791cac61187c completed May 6, 2026, 12:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043cbd3648190b0e8420f961c80b7 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a4046228bf08190abeae852adcb839d completed June 27, 2026, 9:52 p.m.
NED2 Entity disambiguation (via description) batch_6a40467eab3481908a6fb5b61d742925 completed June 27, 2026, 9:54 p.m.
Created at: May 3, 2026, 4:15 p.m.