Triple

T26750838
Position Surface form Disambiguated ID Type / Status
Subject Thomas Massie E674530 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is a common masculine given name of Aramaic origin, widely used in many cultures and historically associated with Christian tradition.
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 Massie, 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 Massie, givenName, Thomas]
Generated description
Thomas is a common masculine given name of Aramaic origin, widely used in many cultures and historically associated with Christian tradition.

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_69eecda6e9dc81908452fab3ba17ed9b completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6188887048190bb119cec6af7a59c completed May 2, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe5e50748190a414fbd300558a6e completed May 23, 2026, 7:22 p.m.
NEDg Description generation batch_6a11ff67f7748190ad1c6874be3660e1 completed May 23, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a11fffd6b1081909ed36e05ffdaed73 completed May 23, 2026, 7:29 p.m.
Created at: April 27, 2026, 3:53 a.m.