Triple

T34642337
Position Surface form Disambiguated ID Type / Status
Subject Chance Perdomo E889594 entity
Predicate notableWork P4 FINISHED
Object Killed by My Debt
Killed by My Debt is a British television drama film that portrays the true story of a young man overwhelmed by escalating debt and aggressive bailiff tactics, highlighting the devastating human impact of financial hardship.
E2106104 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: Killed by My Debt | Statement: [Chance Perdomo, notableWork, Killed by My Debt]
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: Killed by My Debt
Triple: [Chance Perdomo, notableWork, Killed by My Debt]
Generated description
Killed by My Debt is a British television drama film that portrays the true story of a young man overwhelmed by escalating debt and aggressive bailiff tactics, highlighting the devastating human impact of financial hardship.

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_69f349d724848190b63ad3407e0006d9 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f72292f4388190a72cd79d37a244e7 completed May 3, 2026, 10:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3748f1f54081908777c48bff90dbe9 completed June 21, 2026, 2:14 a.m.
NEDg Description generation batch_6a374a087e94819085641e6c5dc797e4 completed June 21, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_6a374ad276b88190a57d90339a2e319e completed June 21, 2026, 2:22 a.m.
Created at: May 1, 2026, 2:04 a.m.