Triple

T34707610
Position Surface form Disambiguated ID Type / Status
Subject Tell Me Lies E1000549 entity
Predicate basedOnWorkAuthor P2806 FINISHED
Object Carola Lovering
Carola Lovering is an American author best known for her contemporary psychological and relationship-driven novels, including the book that inspired the series "Tell Me Lies."
E2118516 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: Carola Lovering | Statement: [Tell Me Lies, basedOnWorkAuthor, Carola Lovering]
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: Carola Lovering
Triple: [Tell Me Lies, basedOnWorkAuthor, Carola Lovering]
Generated description
Carola Lovering is an American author best known for her contemporary psychological and relationship-driven novels, including the book that inspired the series "Tell Me Lies."

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_69f76dab937881909c86f1b9ad50445f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77975a080819087bf81989033947f completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37a89ac3788190999c0527ac0de76c completed June 21, 2026, 9:02 a.m.
NEDg Description generation batch_6a37a9f0384c81908f981df56bb84816 completed June 21, 2026, 9:08 a.m.
NED2 Entity disambiguation (via description) batch_6a37aa70361481909038190d43bc3a72 completed June 21, 2026, 9:10 a.m.
Created at: May 3, 2026, 3:59 p.m.