Triple

T9926019
Position Surface form Disambiguated ID Type / Status
Subject Apache Pig E187922 entity
Predicate executionEngine P9410 FINISHED
Object Tez
Tez is a generalized data processing framework from the Apache Hadoop ecosystem designed to execute complex data-processing tasks efficiently, often used as an underlying engine for higher-level tools like Apache Pig and Hive.
 E829915 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: Tez | Statement: [Apache Pig, executionEngine, Tez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tez
Context triple: [Apache Pig, executionEngine, Tez]
  • A. TEZ
    TEZ is the IATA airport code for Tezpur Airport, a domestic airport serving the city of Tezpur in Assam, India.
  • B. Zeen
    Zeen was a web-based publishing tool that allowed users to easily create and share digital magazines and visual stories online.
  • C. Taznatit
    Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
  • D. Taze
    Taze is the middle name of Charles Taze Russell, the American religious leader who founded the Bible Student movement and was an early influence on Jehovah’s Witnesses.
  • E. Zezuru
    Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
  • 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: Tez
Triple: [Apache Pig, executionEngine, Tez]
Generated description
Tez is a generalized data processing framework from the Apache Hadoop ecosystem designed to execute complex data-processing tasks efficiently, often used as an underlying engine for higher-level tools like Apache Pig and Hive.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tez
Target entity description: Tez is a generalized data processing framework from the Apache Hadoop ecosystem designed to execute complex data-processing tasks efficiently, often used as an underlying engine for higher-level tools like Apache Pig and Hive.
  • A. TEZ
    TEZ is the IATA airport code for Tezpur Airport, a domestic airport serving the city of Tezpur in Assam, India.
  • B. Zeen
    Zeen was a web-based publishing tool that allowed users to easily create and share digital magazines and visual stories online.
  • C. Taznatit
    Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
  • D. Taze
    Taze is the middle name of Charles Taze Russell, the American religious leader who founded the Bible Student movement and was an early influence on Jehovah’s Witnesses.
  • E. Zezuru
    Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
  • 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_69ca82b22a688190b52c75bd48429c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb599e32c8190ac676fa89c131bb6 completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20e143660819097a9fa96365bc25a completed April 5, 2026, 7:24 a.m.
NEDg Description generation batch_69d21318b3008190af5db2bfb53bc2c6 completed April 5, 2026, 7:45 a.m.
NED2 Entity disambiguation (via description) batch_69d213b979e88190ad5a4f72784a0fe6 completed April 5, 2026, 7:48 a.m.
Created at: March 30, 2026, 8:43 p.m.