Triple

T37614113
Position Surface form Disambiguated ID Type / Status
Subject Hubbell Gardiner E935869 entity
Predicate hasRomanticRelationshipWith P9994 FINISHED
Object Katie Morosky
Katie Morosky is a politically passionate, outspoken Jewish activist and the idealistic romantic lead portrayed by Barbra Streisand in the film "The Way We Were."
E258569 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: Katie Morosky | Statement: [Hubbell Gardiner, hasRomanticRelationshipWith, Katie Morosky]
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: Katie Morosky
Triple: [Hubbell Gardiner, hasRomanticRelationshipWith, Katie Morosky]
Generated description
Katie Morosky is a politically passionate, outspoken Jewish activist and the idealistic romantic lead portrayed by Barbra Streisand in the film "The Way We Were."

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_69f76ed16b748190ad6add183b1be688 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba9086f6c81908971d32325bbcfd9 completed May 6, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4167f11ca481908c659e0878583e65 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a416bb629348190a74da4c807a84aab completed June 28, 2026, 6:45 p.m.
NED2 Entity disambiguation (via description) batch_6a416c59fe448190bfe6cffcc42685a9 completed June 28, 2026, 6:47 p.m.
Created at: May 3, 2026, 4:18 p.m.