Triple

T25605799
Position Surface form Disambiguated ID Type / Status
Subject Make Way for Ducklings duck family E641909 entity
Predicate depicts P1581 FINISHED
Object Kack the duckling
Kack the duckling is one of the named duckling characters in Robert McCloskey’s classic children’s book "Make Way for Ducklings."
E1687878 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: Kack the duckling | Statement: [Make Way for Ducklings duck family, depicts, Kack the duckling]
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: Kack the duckling
Triple: [Make Way for Ducklings duck family, depicts, Kack the duckling]
Generated description
Kack the duckling is one of the named duckling characters in Robert McCloskey’s classic children’s book "Make Way for Ducklings."

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_69e75dc6ccf081908d49578fd36a76d5 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9aa9b6881909fd56b8a85534062 completed May 2, 2026, 1:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b77486c88190a6b23c75dede7cb6 completed May 22, 2026, 8:07 p.m.
NEDg Description generation batch_6a10b8652614819087580690269f6a3a completed May 22, 2026, 8:11 p.m.
NED2 Entity disambiguation (via description) batch_6a10b99e39b08190abbe927b4916c0ee completed May 22, 2026, 8:16 p.m.
Created at: April 21, 2026, 4:38 p.m.