Triple

T10915717
Position Surface form Disambiguated ID Type / Status
Subject PEP 636 E257816 entity
Predicate author P4 FINISHED
Object Tal Ben-Nun
Tal Ben-Nun is a computer scientist and software engineer known for his contributions to Python, including co-authoring PEP 636 on structural pattern matching.
E897701 NE FINISHED

How this triple was built (4 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: Tal Ben-Nun | Statement: [PEP 636, author, Tal Ben-Nun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tal Ben-Nun
Context triple: [PEP 636, author, Tal Ben-Nun]
  • A. Haim Oron
    Haim Oron is an Israeli politician and peace activist who led the left-wing Meretz party and served for many years as a member of the Knesset.
  • B. Moshe Aviv
    Moshe Aviv was an Israeli businessman and real estate developer best known for his major role in shaping modern Israeli urban skylines.
  • C. Ehud Brog
    Ehud Brog is the birth name of Ehud Barak, a former Prime Minister and Defense Minister of Israel and one of the country’s most decorated military officers.
  • D. Amir Yaron
    Amir Yaron is an Israeli-American economist who serves as the Governor of the Bank of Israel, overseeing the country’s monetary policy and financial stability.
  • E. Uri Tadmor
    Uri Tadmor is a linguist known for his research on Austronesian languages, particularly the Lamaholot language of eastern Indonesia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Tal Ben-Nun
Triple: [PEP 636, author, Tal Ben-Nun]
Generated description
Tal Ben-Nun is a computer scientist and software engineer known for his contributions to Python, including co-authoring PEP 636 on structural pattern matching.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tal Ben-Nun
Target entity description: Tal Ben-Nun is a computer scientist and software engineer known for his contributions to Python, including co-authoring PEP 636 on structural pattern matching.
  • A. Haim Oron
    Haim Oron is an Israeli politician and peace activist who led the left-wing Meretz party and served for many years as a member of the Knesset.
  • B. Moshe Aviv
    Moshe Aviv was an Israeli businessman and real estate developer best known for his major role in shaping modern Israeli urban skylines.
  • C. Ehud Brog
    Ehud Brog is the birth name of Ehud Barak, a former Prime Minister and Defense Minister of Israel and one of the country’s most decorated military officers.
  • D. Amir Yaron
    Amir Yaron is an Israeli-American economist who serves as the Governor of the Bank of Israel, overseeing the country’s monetary policy and financial stability.
  • E. Uri Tadmor
    Uri Tadmor is a linguist known for his research on Austronesian languages, particularly the Lamaholot language of eastern Indonesia.
  • F. None of above. chosen

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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d77074c77c8190af91369eee11f1b7 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e34455ea4c8190b6f2433f3f745b76 completed April 18, 2026, 8:44 a.m.
NEDg Description generation batch_69e3556ad7ec819095b3babc67ecdfd4 completed April 18, 2026, 9:56 a.m.
NED2 Entity disambiguation (via description) batch_69e358f860f08190bfd10519ff3806aa completed April 18, 2026, 10:12 a.m.
Created at: April 8, 2026, 9:22 p.m.