Triple

T24710625
Position Surface form Disambiguated ID Type / Status
Subject Albert Delpy E612014 entity
Predicate notableWork P4 FINISHED
Object The Rabbi’s Cat
The Rabbi’s Cat is a French animated film (adapted from Joann Sfar’s graphic novel) about a talking cat in 1920s Algeria that explores religion, identity, and coexistence with humor and philosophical depth.
 E1646976 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 Rabbi’s Cat | Statement: [Albert Delpy, notableWork, The Rabbi’s Cat]
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 Rabbi’s Cat
Triple: [Albert Delpy, notableWork, The Rabbi’s Cat]
Generated description
The Rabbi’s Cat is a French animated film (adapted from Joann Sfar’s graphic novel) about a talking cat in 1920s Algeria that explores religion, identity, and coexistence with humor and philosophical depth.

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_69e2c4d9c24c8190a3712d74327f0c6e completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40ff994088190bf836b84275dba38 completed May 1, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10100f9fb88190bc8dd0e13ba01595 completed May 22, 2026, 8:13 a.m.
NEDg Description generation batch_6a10136c6ea88190804695a63f4bf0fd completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a1013c36d648190b0dda9f111eff61d completed May 22, 2026, 8:28 a.m.
Created at: April 18, 2026, 3:24 a.m.