Triple

T29040336
Position Surface form Disambiguated ID Type / Status
Subject Wasserman E737976 entity
Predicate usedBy P260 FINISHED
Object Sam Wasserman
Sam Wasserman is an individual whose name is associated with the use of the Wasserman system or concept referenced in the given context.
E1977212 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: Sam Wasserman | Statement: [Wasserman, usedBy, Sam Wasserman]
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: Sam Wasserman
Triple: [Wasserman, usedBy, Sam Wasserman]
Generated description
Sam Wasserman is an individual whose name is associated with the use of the Wasserman system or concept referenced in the given context.

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_69f077efb3848190b41574e1670f6ae2 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f66040274c8190a7c9f08182edc8b7 completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d269fc88190b07fe448a88a726e completed June 13, 2026, 6:10 p.m.
NEDg Description generation batch_6a2d9e2593f4819092c89187e84af3c9 completed June 13, 2026, 6:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2d9f083f0481909184bb37c1ce0e7a completed June 13, 2026, 6:18 p.m.
Created at: April 28, 2026, 10:01 a.m.