Triple

T35711450
Position Surface form Disambiguated ID Type / Status
Subject Roberto Reyes E1031869 entity
Predicate sharesTitleWith P29696 FINISHED
Object Alejandra Jones
Alejandra Jones is a Marvel Comics character who, like Roberto Reyes, assumes the mantle of Ghost Rider.
E2177917 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: Alejandra Jones | Statement: [Roberto Reyes, sharesTitleWith, Alejandra Jones]
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: Alejandra Jones
Triple: [Roberto Reyes, sharesTitleWith, Alejandra Jones]
Generated description
Alejandra Jones is a Marvel Comics character who, like Roberto Reyes, assumes the mantle of Ghost Rider.

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_69f76e0df1d08190965b1c6dff94c391 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a0f5779481908db9c67125100ab4 completed May 3, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a397d64825481909323a3599f552dd4 completed June 22, 2026, 6:22 p.m.
NEDg Description generation batch_6a39806f24348190ba962eb2b7a9a946 completed June 22, 2026, 6:35 p.m.
NED2 Entity disambiguation (via description) batch_6a3980c8c7408190ab149a160ed64bc5 completed June 22, 2026, 6:36 p.m.
Created at: May 3, 2026, 4:05 p.m.