Triple

T37555007
Position Surface form Disambiguated ID Type / Status
Subject Theater of Pain E933674 entity
Predicate associatedCovenant P58660 FINISHED
Object Necrolord E2240372 NE FINISHED

How this triple was built (1 step)

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: Necrolord | Statement: [Theater of Pain, associatedCovenant, Necrolord]

Provenance (3 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_69f76eca55bc8190acf25741793d5dac completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_6a03809e663c819080cff52d0377d81f completed May 12, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4256cbfdc08190bde47ef92a78408f completed June 29, 2026, 11:28 a.m.
Created at: May 3, 2026, 4:17 p.m.