Triple

T35818941
Position Surface form Disambiguated ID Type / Status
Subject Richard Wiseman E1035442 entity
Predicate notableWork P4 FINISHED
Object The Luck Factor
The Luck Factor is a popular psychology book by Richard Wiseman that explores the science behind why some people appear luckier than others and how to enhance one’s own luck through specific attitudes and behaviors.
E2156943 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 Luck Factor | Statement: [Richard Wiseman, notableWork, The Luck Factor]
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 Luck Factor
Triple: [Richard Wiseman, notableWork, The Luck Factor]
Generated description
The Luck Factor is a popular psychology book by Richard Wiseman that explores the science behind why some people appear luckier than others and how to enhance one’s own luck through specific attitudes and behaviors.

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_69f76e185ffc8190880b3cdf51decd38 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a8fd03c88190b3976b3d5314d0a3 completed May 3, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3891792bf0819098f892061f2249ab completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a3892e5fa348190b35dd8a56a58fe77 completed June 22, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_6a3893bd25d08190baec1829bc399979 completed June 22, 2026, 1:45 a.m.
Created at: May 3, 2026, 4:06 p.m.