Triple

T36258071
Position Surface form Disambiguated ID Type / Status
Subject A Tale of Love and Darkness (film) E891998 entity
Predicate basedOn P98 FINISHED
Object A Tale of Love and Darkness (novel)
A Tale of Love and Darkness is Amos Oz’s autobiographical novel recounting his childhood in Jerusalem, his family’s struggles, and the early years of the State of Israel.
E2179594 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: A Tale of Love and Darkness (novel) | Statement: [A Tale of Love and Darkness (film), basedOn, A Tale of Love and Darkness (novel)]
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: A Tale of Love and Darkness (novel)
Triple: [A Tale of Love and Darkness (film), basedOn, A Tale of Love and Darkness (novel)]
Generated description
A Tale of Love and Darkness is Amos Oz’s autobiographical novel recounting his childhood in Jerusalem, his family’s struggles, and the early years of the State of Israel.

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_69f76e4599108190811532e707d6bc2c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b5fece288190bd538ba5391d45e7 completed May 3, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a30fd408819089ac87de6d3e812d completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a4f1cf308190a2f4cd5dc44ee654 completed June 22, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a39a67257f481908b4a38100c5d64d9 completed June 22, 2026, 9:17 p.m.
Created at: May 3, 2026, 4:09 p.m.