Triple

T38478154
Position Surface form Disambiguated ID Type / Status
Subject Inferno (The Ultimate Doom episode) E915600 entity
Predicate hasPart P35 FINISHED
Object E3M2: Slough of Despair
E3M2: Slough of Despair is a single-player level in the third episode of the original Doom, notable for its distinctive hand-shaped layout and hellish, trap-filled design.
E2272121 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: E3M2: Slough of Despair | Statement: [Inferno (The Ultimate Doom episode), hasPart, E3M2: Slough of Despair]
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: E3M2: Slough of Despair
Triple: [Inferno (The Ultimate Doom episode), hasPart, E3M2: Slough of Despair]
Generated description
E3M2: Slough of Despair is a single-player level in the third episode of the original Doom, notable for its distinctive hand-shaped layout and hellish, trap-filled 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.