Triple

T28601636
Position Surface form Disambiguated ID Type / Status
Subject Molly Lamont E723927 entity
Predicate appearedIn P795 FINISHED
Object The Man Who Lived Twice
The Man Who Lived Twice is a 1936 American crime drama film about a criminal who undergoes plastic surgery and attempts to reform under a new identity.
 E1826570 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 Man Who Lived Twice | Statement: [Molly Lamont, appearedIn, The Man Who Lived Twice]
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 Man Who Lived Twice
Triple: [Molly Lamont, appearedIn, The Man Who Lived Twice]
Generated description
The Man Who Lived Twice is a 1936 American crime drama film about a criminal who undergoes plastic surgery and attempts to reform under a new identity.

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_69f01d80b1908190980594837604b8c7 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f65216efc881908c9f89626ef0da8b completed May 2, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb703bca48190b1ff54262fb7a12f completed May 31, 2026, 10:32 p.m.
NEDg Description generation batch_6a1cbaaa69348190a4e8de0490e66edf completed May 31, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a1cbb5d90ec819093705eae50314f33 completed May 31, 2026, 10:51 p.m.
Created at: April 28, 2026, 4:24 a.m.