Triple

T23827977
Position Surface form Disambiguated ID Type / Status
Subject Incident at Neshabur E589431 entity
Predicate composer P1361 FINISHED
Object Alberto Gianquinto
Alberto Gianquinto was an American jazz and rock pianist and composer best known for his work with Carlos Santana, including co-writing the song "Incident at Neshabur."
E2292075 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: Alberto Gianquinto | Statement: [Incident at Neshabur, composer, Alberto Gianquinto]
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: Alberto Gianquinto
Triple: [Incident at Neshabur, composer, Alberto Gianquinto]
Generated description
Alberto Gianquinto was an American jazz and rock pianist and composer best known for his work with Carlos Santana, including co-writing the song "Incident at Neshabur."

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_69e25d1922d481909cab567c06a802ab completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7f304f08190bd965df06f013b3f completed April 29, 2026, 8:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5cbb9fba208190a8c89adc08ff3fbd completed July 19, 2026, 11:57 a.m.
NEDg Description generation batch_6a5cbc19ad70819091b041d57ea1df1d completed July 19, 2026, 11:59 a.m.
NED2 Entity disambiguation (via description) batch_6a5cbc728d748190a5470818c88c132b completed July 19, 2026, noon
Created at: April 17, 2026, 8 p.m.