Triple

T38010521
Position Surface form Disambiguated ID Type / Status
Subject Charles Dickens bibliography E948350 entity
Predicate includesWork P2011 FINISHED
Object The Trial for Murder
"The Trial for Murder" is a short ghost story by Charles Dickens that blends supernatural elements with a courtroom drama to explore themes of justice and guilt.
E2251454 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 Trial for Murder | Statement: [Charles Dickens bibliography, includesWork, The Trial for Murder]
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 Trial for Murder
Triple: [Charles Dickens bibliography, includesWork, The Trial for Murder]
Generated description
"The Trial for Murder" is a short ghost story by Charles Dickens that blends supernatural elements with a courtroom drama to explore themes of justice and guilt.

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_69f76efb4b10819092c8c2ba28ac06a8 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc944694481909f50a54379636f35 completed May 6, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a412ccb9ea48190aacfac4f09b31ae0 completed June 28, 2026, 2:16 p.m.
NEDg Description generation batch_6a412dd5b1b8819096f0bc7cb50e423e completed June 28, 2026, 2:21 p.m.
NED2 Entity disambiguation (via description) batch_6a412e29958481909226c3d74ed27770 completed June 28, 2026, 2:22 p.m.
Created at: May 3, 2026, 4:20 p.m.