Triple

T35507218
Position Surface form Disambiguated ID Type / Status
Subject Ursula Hegi E1026182 entity
Predicate notableWork P4 FINISHED
Object Stones from the River
Stones from the River is a historical novel by Ursula Hegi that follows the life of a dwarf woman in a small German town before, during, and after the Nazi era, exploring themes of otherness, complicity, and moral courage.
 E2145157 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: Stones from the River | Statement: [Ursula Hegi, notableWork, Stones from the River]
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: Stones from the River
Triple: [Ursula Hegi, notableWork, Stones from the River]
Generated description
Stones from the River is a historical novel by Ursula Hegi that follows the life of a dwarf woman in a small German town before, during, and after the Nazi era, exploring themes of otherness, complicity, and moral courage.

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_69f76dfd61208190b93ec6dc439cab41 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7976f6e08819086e14addec404ae0 completed May 3, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a32c8d48190aa0cb6f32e76e1d8 completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384aa84b748190824a5fa4f797bdca completed June 21, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_6a384e5cdc388190b78a84212c06a3ee completed June 21, 2026, 8:49 p.m.
Created at: May 3, 2026, 4:04 p.m.