Triple

T38466193
Position Surface form Disambiguated ID Type / Status
Subject Zimbabwean literature E912571 entity
Predicate hasNotableWork P4 FINISHED
Object Under the Tongue
"Under the Tongue" is a critically acclaimed Zimbabwean novel by Yvonne Vera that explores trauma, memory, and silence through the fragmented voice of a young girl in postcolonial Zimbabwe.
 E2271481 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: Under the Tongue | Statement: [Zimbabwean literature, hasNotableWork, Under the Tongue]
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: Under the Tongue
Triple: [Zimbabwean literature, hasNotableWork, Under the Tongue]
Generated description
"Under the Tongue" is a critically acclaimed Zimbabwean novel by Yvonne Vera that explores trauma, memory, and silence through the fragmented voice of a young girl in postcolonial Zimbabwe.

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_69f76e861d8c81908559031dc66e3c15 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd1facbcc8190af0faa49f68f6904 completed May 7, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ccb715d08190aa11a361c828adae completed June 29, 2026, 1:39 a.m.
NEDg Description generation batch_6a41ce4186748190a7a24dbfc4f8e0f4 completed June 29, 2026, 1:45 a.m.
NED2 Entity disambiguation (via description) batch_6a41cec6e9b081909c2036bd142be990 completed June 29, 2026, 1:47 a.m.
Created at: May 3, 2026, 4:31 p.m.