Triple

T27873224
Position Surface form Disambiguated ID Type / Status
Subject Jake Willemain E704846 entity
Predicate notableWork P4 FINISHED
Object Put Yourself in My Shoes
Put Yourself in My Shoes is a notable work by author Jake Willemain, recognized for its engaging exploration of perspective and empathy.
 E1824133 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: Put Yourself in My Shoes | Statement: [Jake Willemain, notableWork, Put Yourself in My Shoes]
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: Put Yourself in My Shoes
Triple: [Jake Willemain, notableWork, Put Yourself in My Shoes]
Generated description
Put Yourself in My Shoes is a notable work by author Jake Willemain, recognized for its engaging exploration of perspective and empathy.

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_69ef84111bb4819084298f994b31c62f completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6397dce7c819095d1b64ae7c0fef8 completed May 2, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6c212e481908c8ddfb405192aba completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cb96552ec81909b935bb4b46913ec completed May 31, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_6a1cb9c3e8e88190bf5c5955adf18073 completed May 31, 2026, 10:44 p.m.
Created at: April 27, 2026, 6:25 p.m.