Triple

T28041360
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Anne Caplan E708547 entity
Predicate notableWork P4 FINISHED
Object The Night Before
The Night Before is a 2015 American Christmas-themed stoner comedy film starring Joseph Gordon-Levitt, Seth Rogen, and Anthony Mackie as longtime friends on one last wild holiday night in New York City.
E740611 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 Night Before | Statement: [Elizabeth Anne Caplan, notableWork, The Night Before]
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 Night Before
Triple: [Elizabeth Anne Caplan, notableWork, The Night Before]
Generated description
The Night Before is a 2015 American Christmas-themed stoner comedy film starring Joseph Gordon-Levitt, Seth Rogen, and Anthony Mackie as longtime friends on one last wild holiday night in New York City.

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_69ef9b6cf538819094a633ffa67afec1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63f307b1481909612232b4b659841 completed May 2, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8bad8d08190b8ff2b65162bc2d9 completed May 26, 2026, 3:14 p.m.
NEDg Description generation batch_6a15bcca3074819084e5661a3616cbfc completed May 26, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_6a15bd774d4c819093f2999c2ae8e52e completed May 26, 2026, 3:34 p.m.
Created at: April 27, 2026, 8:25 p.m.