Triple

T36349697
Position Surface form Disambiguated ID Type / Status
Subject I Am Mother E895163 entity
Predicate screenwriter P2831 FINISHED
Object Michael Lloyd Green
Michael Lloyd Green is a screenwriter best known for writing the science fiction thriller film "I Am Mother."
E2179708 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: Michael Lloyd Green | Statement: [I Am Mother, screenwriter, Michael Lloyd Green]
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: Michael Lloyd Green
Triple: [I Am Mother, screenwriter, Michael Lloyd Green]
Generated description
Michael Lloyd Green is a screenwriter best known for writing the science fiction thriller film "I Am Mother."

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_69f76e4f437c8190a1af3ea2564f41f5 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7baa404348190ac14f33f5b6320d7 completed May 3, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39a327b1a08190b92ca04777088972 completed June 22, 2026, 9:03 p.m.
NEDg Description generation batch_6a39a40c7d908190b5981106babcfbb7 completed June 22, 2026, 9:07 p.m.
NED2 Entity disambiguation (via description) batch_6a39a6b290148190b8e4649efd67a390 completed June 22, 2026, 9:18 p.m.
Created at: May 3, 2026, 4:09 p.m.