Triple

T23809614
Position Surface form Disambiguated ID Type / Status
Subject Dinesh D’Souza E589809 entity
Predicate notableWork P4 FINISHED
Object What’s So Great About America
"What’s So Great About America" is a political commentary book by conservative author Dinesh D’Souza that defends American values and institutions against their critics.
 E1605937 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: What’s So Great About America | Statement: [Dinesh D’Souza, notableWork, What’s So Great About America]
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: What’s So Great About America
Triple: [Dinesh D’Souza, notableWork, What’s So Great About America]
Generated description
"What’s So Great About America" is a political commentary book by conservative author Dinesh D’Souza that defends American values and institutions against their critics.

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_69e25d19fecc8190a5cf39bbb18d5d7f completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7549c44819099b9e7eb36747f38 completed April 29, 2026, 8:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f697e5bac819082c27676a7184ee4 completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6d3ea7a0819098e47bce047df2c7 completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6e5bceb88190ae077c6b68bc25c1 completed May 21, 2026, 8:43 p.m.
Created at: April 17, 2026, 7:56 p.m.