Triple

T23894933
Position Surface form Disambiguated ID Type / Status
Subject Paris Geller E600876 entity
Predicate romanticallyInvolvedWith P9994 FINISHED
Object Doyle McMaster
Doyle McMaster is a witty, ambitious Yale Daily News editor and later journalist from the television series "Gilmore Girls," known for his fast-talking banter and long-term relationship with Paris Geller.
E1609000 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: Doyle McMaster | Statement: [Paris Geller, romanticallyInvolvedWith, Doyle McMaster]
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: Doyle McMaster
Triple: [Paris Geller, romanticallyInvolvedWith, Doyle McMaster]
Generated description
Doyle McMaster is a witty, ambitious Yale Daily News editor and later journalist from the television series "Gilmore Girls," known for his fast-talking banter and long-term relationship with Paris Geller.

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_69e295341ac0819080647f2908af793c completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cdd857d081908740c4abb246c2ba completed April 29, 2026, 9:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7628a4cc819097b6de77d692dc1a completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f77b76ab08190b2caf42777492249 completed May 21, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_6a0f788c4c108190b79e1ea898be2a80 completed May 21, 2026, 9:26 p.m.
Created at: April 17, 2026, 8:25 p.m.