Triple

T24302801
Position Surface form Disambiguated ID Type / Status
Subject Ali Pfefferman E612442 entity
Predicate hasRomanticRelationshipWith P9994 FINISHED
Object Syd Feldman
Syd Feldman is a character on the television series "Transparent," known as Ali Pfefferman’s close friend and later romantic partner.
E1701888 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: Syd Feldman | Statement: [Ali Pfefferman, hasRomanticRelationshipWith, Syd Feldman]
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: Syd Feldman
Triple: [Ali Pfefferman, hasRomanticRelationshipWith, Syd Feldman]
Generated description
Syd Feldman is a character on the television series "Transparent," known as Ali Pfefferman’s close friend and later romantic partner.

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_69e2d7d91bb48190bc5377d17a85fb21 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292239aa88190847e78ffd31eab4e completed April 29, 2026, 11:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec75c29c8190a214a4fcc5358010 completed May 22, 2026, 11:53 p.m.
NEDg Description generation batch_6a10ee8e2a008190962a88ee42e3c741 completed May 23, 2026, 12:02 a.m.
NED2 Entity disambiguation (via description) batch_6a10f02156908190aa1fb061ae251f82 completed May 23, 2026, 12:09 a.m.
Created at: April 18, 2026, 1:27 a.m.