Triple

T29782586
Position Surface form Disambiguated ID Type / Status
Subject Edna Rae Gillooly E756161 entity
Predicate notableWork P4 FINISHED
Object The Exorcist
The Exorcist is a landmark 1971 horror novel by William Peter Blatty, later adapted into a hugely influential 1973 film, that centers on the demonic possession of a young girl and the priests who attempt to save her.
E1408481 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 Exorcist | Statement: [Edna Rae Gillooly, notableWork, The Exorcist]
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 Exorcist
Triple: [Edna Rae Gillooly, notableWork, The Exorcist]
Generated description
The Exorcist is a landmark 1971 horror novel by William Peter Blatty, later adapted into a hugely influential 1973 film, that centers on the demonic possession of a young girl and the priests who attempt to save her.

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_69f22451fb748190bbdbab401280affb completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f674a715b48190b2c59ce71a8320dd completed May 2, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8ffe490819085e17a59638932fa completed June 8, 2026, 1:52 p.m.
NEDg Description generation batch_6a26cda9e7b88190861c905b18256801 completed June 8, 2026, 2:11 p.m.
NED2 Entity disambiguation (via description) batch_6a26d3faa9d08190aa5f45736d43db74 completed June 8, 2026, 2:38 p.m.
Created at: April 29, 2026, 5:06 p.m.