Triple

T29965241
Position Surface form Disambiguated ID Type / Status
Subject Guns Don’t Kill People… Lazers Do E761163 entity
Predicate hasPart P35 FINISHED
Object Lazer Theme
Lazer Theme is a track by the Welsh rap group Goldie Lookin Chain from their album "Guns Don’t Kill People… Lazers Do," showcasing their comedic, irreverent hip hop style.
E1894436 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: Lazer Theme | Statement: [Guns Don’t Kill People… Lazers Do, hasPart, Lazer Theme]
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: Lazer Theme
Triple: [Guns Don’t Kill People… Lazers Do, hasPart, Lazer Theme]
Generated description
Lazer Theme is a track by the Welsh rap group Goldie Lookin Chain from their album "Guns Don’t Kill People… Lazers Do," showcasing their comedic, irreverent hip hop style.

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_69f22466327481908ba6db916837bece completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67868e8548190bc34423005da2c0c completed May 2, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2721f1d86c8190b285e4a1225ac7c2 completed June 8, 2026, 8:11 p.m.
NEDg Description generation batch_6a272333f384819084456b384bc17a6c completed June 8, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2723e6c6648190801fec9c9fd7f557 completed June 8, 2026, 8:19 p.m.
Created at: April 29, 2026, 6:30 p.m.