Triple

T30672704
Position Surface form Disambiguated ID Type / Status
Subject Jonas E780833 entity
Predicate settingUniverse P16450 FINISHED
Object the Community in The Giver
The Community in *The Giver* is a tightly controlled, seemingly utopian society that has eliminated pain, choice, and deep emotion through strict rules, surveillance, and the suppression of memory.
 E1930383 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: the Community in The Giver | Statement: [Jonas, settingUniverse, the Community in The Giver]
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: the Community in The Giver
Triple: [Jonas, settingUniverse, the Community in The Giver]
Generated description
The Community in *The Giver* is a tightly controlled, seemingly utopian society that has eliminated pain, choice, and deep emotion through strict rules, surveillance, and the suppression of memory.

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_69f224a7fc208190a07d6d3879b31640 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68b159e3881908e7d125ae27eab41 completed May 2, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b07f0c448190bee14ad07855ac96 completed June 10, 2026, 12:31 a.m.
NEDg Description generation batch_6a28b1cd9e78819093ff46123d12a12e completed June 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2b51afc81908cae8756f6d9b3a1 completed June 10, 2026, 12:41 a.m.
Created at: April 29, 2026, 8:32 p.m.