Triple

T33853892
Position Surface form Disambiguated ID Type / Status
Subject David Rabe E867712 entity
Predicate notableWork P4 FINISHED
Object In the Boom Boom Room
In the Boom Boom Room is a dark, character-driven stage play by David Rabe that explores themes of exploitation, identity, and disillusionment in 1960s American nightlife.
 E2070762 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: In the Boom Boom Room | Statement: [David Rabe, notableWork, In the Boom Boom Room]
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: In the Boom Boom Room
Triple: [David Rabe, notableWork, In the Boom Boom Room]
Generated description
In the Boom Boom Room is a dark, character-driven stage play by David Rabe that explores themes of exploitation, identity, and disillusionment in 1960s American nightlife.

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_69f349943ccc8190a3c41a3e0ae46cbf completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70076bdec8190a109af85bed04c90 completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a367616ffb48190a0631e7ba124dce4 completed June 20, 2026, 11:14 a.m.
NEDg Description generation batch_6a36768b3b548190bd5d62b1fc904d6a completed June 20, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_6a36772ae3308190849be7395a7adcde completed June 20, 2026, 11:19 a.m.
Created at: May 1, 2026, 1:47 a.m.