Triple

T28231561
Position Surface form Disambiguated ID Type / Status
Subject Private: The Chicago Story E711756 entity
Predicate basedOn P98 FINISHED
Object the Private book series universe
The Private book series universe is a young adult mystery-drama world centered on elite prep schools, dark secrets, and high-stakes social intrigue.
 E1808634 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: the Private book series universe | Statement: [Private: The Chicago Story, basedOn, the Private book series universe]
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: the Private book series universe
Triple: [Private: The Chicago Story, basedOn, the Private book series universe]
Generated description
The Private book series universe is a young adult mystery-drama world centered on elite prep schools, dark secrets, and high-stakes social intrigue.

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_69efb51ece308190b8c269a057e36652 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f6438893788190913a9ca14a3c43fc completed May 2, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6cbb46c8190939585074fe195b3 completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15e8052d5c8190961fc496e0d44bbd completed May 26, 2026, 6:35 p.m.
NED2 Entity disambiguation (via description) batch_6a15f13a24cc8190ae9d36e9d4a38454 completed May 26, 2026, 7:15 p.m.
Created at: April 27, 2026, 10:52 p.m.