Triple

T38478052
Position Surface form Disambiguated ID Type / Status
Subject Knee-Deep in the Dead E915598 entity
Predicate containsLevel P89909 FINISHED
Object E1M3: Toxin Refinery
E1M3: Toxin Refinery is a classic industrial-themed level from the first episode of the original Doom, known for its toxic waste pits, secret areas, and early showcase of the game's maze-like design.
E2272106 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: E1M3: Toxin Refinery | Statement: [Knee-Deep in the Dead, containsLevel, E1M3: Toxin Refinery]
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: E1M3: Toxin Refinery
Triple: [Knee-Deep in the Dead, containsLevel, E1M3: Toxin Refinery]
Generated description
E1M3: Toxin Refinery is a classic industrial-themed level from the first episode of the original Doom, known for its toxic waste pits, secret areas, and early showcase of the game's maze-like design.

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_69f76e8ff5cc8190a88803369183845e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd22075688190ab06fb686c520fa4 completed May 7, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ccc099ec819081d90128bb38d1c0 completed June 29, 2026, 1:39 a.m.
NEDg Description generation batch_6a41cdbe47f08190b18cc238cabca598 completed June 29, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a41ce4cee4481909d34941327630fb7 completed June 29, 2026, 1:45 a.m.
Created at: May 3, 2026, 4:31 p.m.