Triple

T30670134
Position Surface form Disambiguated ID Type / Status
Subject Cold Station 12 E780770 entity
Predicate featuresCharacter P626 FINISHED
Object Dr. Jeremy Lucas
Dr. Jeremy Lucas is a Starfleet medical researcher and close colleague of Dr. Phlox who appears in the Star Trek: Enterprise episode "Cold Station 12."
E1932145 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: Dr. Jeremy Lucas | Statement: [Cold Station 12, featuresCharacter, Dr. Jeremy Lucas]
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: Dr. Jeremy Lucas
Triple: [Cold Station 12, featuresCharacter, Dr. Jeremy Lucas]
Generated description
Dr. Jeremy Lucas is a Starfleet medical researcher and close colleague of Dr. Phlox who appears in the Star Trek: Enterprise episode "Cold Station 12."

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_69f224a7fc208190a07d6d3879b31640 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68b13a304819095432c1f76be1c6f completed May 2, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b07f0c448190bee14ad07855ac96 completed June 10, 2026, 12:31 a.m.
NEDg Description generation batch_6a28b1cd9e78819093ff46123d12a12e completed June 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2b2c9fc8190af8deaeceb76e5f9 completed June 10, 2026, 12:41 a.m.
Created at: April 29, 2026, 8:31 p.m.