Triple

T30713771
Position Surface form Disambiguated ID Type / Status
Subject Thomas Bailey Aldrich E781966 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is a masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many cultures and languages.
E67625 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: Thomas | Statement: [Thomas Bailey Aldrich, givenName, Thomas]
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: Thomas
Triple: [Thomas Bailey Aldrich, givenName, Thomas]
Generated description
Thomas is a masculine given name of Aramaic origin, traditionally interpreted to mean "twin" and widely used in many cultures and languages.

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_69f224acd24481908ed5f96f0d69b5dd completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c20d09481908f566241722507d3 completed May 2, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbcccf1881908324d3c685aa9787 completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc580ea08190848e95bff35a2ab0 completed June 10, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a28bcf1f5d081908823910cd023c991 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:35 p.m.