Triple

T25000669
Position Surface form Disambiguated ID Type / Status
Subject Mary Stilwell Edison E625708 entity
Predicate alsoKnownAs P39 FINISHED
Object Mary Edison
Mary Edison, born Mary Stilwell, was the first wife of inventor Thomas Edison and the mother of three of his children.
E1659503 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: Mary Edison | Statement: [Mary Stilwell Edison, alsoKnownAs, Mary Edison]
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: Mary Edison
Triple: [Mary Stilwell Edison, alsoKnownAs, Mary Edison]
Generated description
Mary Edison, born Mary Stilwell, was the first wife of inventor Thomas Edison and the mother of three of his children.

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_69e2ff26c50481908bc82e799c9e6587 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44b0b35048190ae886a4fd5d385a7 completed May 1, 2026, 6:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10336ecc4c8190b4a747d9794e9294 completed May 22, 2026, 10:43 a.m.
NEDg Description generation batch_6a10347d3dd08190958287952b3bd5fe completed May 22, 2026, 10:48 a.m.
NED2 Entity disambiguation (via description) batch_6a10351c0c0081909453f67b06668188 completed May 22, 2026, 10:51 a.m.
Created at: April 18, 2026, 6:04 a.m.