Triple

T17216284
Position Surface form Disambiguated ID Type / Status
Subject Andrew Sachs E417860 entity
Predicate birthName P65 FINISHED
Object Andreas Siegfried Sachs
Andreas Siegfried Sachs, better known as Andrew Sachs, was a German-born British actor and comedian best known for playing the hapless waiter Manuel in the classic sitcom "Fawlty Towers."
E1833172 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: Andreas Siegfried Sachs | Statement: [Andrew Sachs, birthName, Andreas Siegfried Sachs]
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: Andreas Siegfried Sachs
Triple: [Andrew Sachs, birthName, Andreas Siegfried Sachs]
Generated description
Andreas Siegfried Sachs, better known as Andrew Sachs, was a German-born British actor and comedian best known for playing the hapless waiter Manuel in the classic sitcom "Fawlty Towers."

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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dc9f96881909eb86786a76e17e4 completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a24a21eb1508190b19f09eb132751b8 completed June 6, 2026, 10:41 p.m.
NEDg Description generation batch_6a24a650b8408190abe70dc1108b8368 completed June 6, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_6a24aa401b2c8190bf774922baa12667 completed June 6, 2026, 11:16 p.m.
Created at: April 10, 2026, 5:38 a.m.