Triple

T37810061
Position Surface form Disambiguated ID Type / Status
Subject Against the Law E942615 entity
Predicate writtenBy P806 FINISHED
Object Nancy Allen
Nancy Allen is an American author known for writing legal thrillers and crime novels, often drawing on her background as a prosecutor.
E2281746 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: Nancy Allen | Statement: [Against the Law, writtenBy, Nancy Allen]
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: Nancy Allen
Triple: [Against the Law, writtenBy, Nancy Allen]
Generated description
Nancy Allen is an American author known for writing legal thrillers and crime novels, often drawing on her background as a prosecutor.

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_69f76ee8104c8190ab17133ccd8f86e6 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb19c4f6c8190a1e09bad3c849ed5 completed May 6, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4205a837308190bd6f7daf27e48f55 completed June 29, 2026, 5:42 a.m.
NEDg Description generation batch_6a42088459848190bc54e605e2dd1762 completed June 29, 2026, 5:54 a.m.
NED2 Entity disambiguation (via description) batch_6a4208d274ec81909de09c6a9089c00a completed June 29, 2026, 5:55 a.m.
Created at: May 3, 2026, 4:19 p.m.