Triple

T788416
Position Surface form Disambiguated ID Type / Status
Subject Resurrection E16855 entity
Predicate firstPublisher P7323 FINISHED
Object Niva
Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
 E94317 NE FINISHED

How this triple was built (4 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: Niva | Statement: [Resurrection, firstPublisher, Niva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Niva
Context triple: [Resurrection, firstPublisher, Niva]
  • A. Maxus
    Maxus is a commercial vehicle brand known for producing vans, pickups, and light trucks, owned by the Chinese automotive giant SAIC Motor.
  • B. Bilen
    Bilen is a Cushitic language spoken primarily by the Bilen people in central Eritrea.
  • C. Qashqai
    Qashqai is a Turkic language variety spoken primarily by the Qashqai people in southwestern Iran, closely related to Azerbaijani.
  • D. DeSoto
    DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
  • E. Winnebago
    Winnebago is the former English name for the Ho-Chunk, a Native American people originally from the Wisconsin and Illinois region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Niva
Triple: [Resurrection, firstPublisher, Niva]
Generated description
Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Niva
Target entity description: Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
  • A. Maxus
    Maxus is a commercial vehicle brand known for producing vans, pickups, and light trucks, owned by the Chinese automotive giant SAIC Motor.
  • B. Bilen
    Bilen is a Cushitic language spoken primarily by the Bilen people in central Eritrea.
  • C. Qashqai
    Qashqai is a Turkic language variety spoken primarily by the Qashqai people in southwestern Iran, closely related to Azerbaijani.
  • D. DeSoto
    DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
  • E. Winnebago
    Winnebago is the former English name for the Ho-Chunk, a Native American people originally from the Wisconsin and Illinois region.
  • F. None of above. chosen

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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a782fe988190966b958673fe12bf completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a67efd612481909580fbef3605dcbc completed March 3, 2026, 6:26 a.m.
NEDg Description generation batch_69a67f5a246481908bde953b245a6b5e completed March 3, 2026, 6:27 a.m.
NED2 Entity disambiguation (via description) batch_69a6808fe5748190b95959ee23ee6241 completed March 3, 2026, 6:32 a.m.
Created at: March 1, 2026, 7:38 p.m.