Triple

T14409900
Position Surface form Disambiguated ID Type / Status
Subject Turk E357295 entity
Predicate givenName P17 FINISHED
Object Tab
Tab Turk is an individual whose given name is Tab, likely used as a personal or professional identifier.
E1098099 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: Tab | Statement: [Turk, givenName, Tab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tab
Context triple: [Turk, givenName, Tab]
  • A. TAB
    TAB is the abbreviation for the United Nations Technical Assistance Board, a UN body historically responsible for coordinating technical aid and development assistance to member countries.
  • B. TAB
    TAB is the IATA airport code for A.N.R. Robinson International Airport, the main international gateway to the island of Tobago in Trinidad and Tobago.
  • C. TABS
    TABS is a membership organization that represents and supports college-preparatory boarding schools through advocacy, research, and professional development.
  • D. TABSO
    TABSO was the former national airline of Bulgaria that operated during the socialist era before being reorganized into Balkan Bulgarian Airlines.
  • E. Tap
    Tap is a 1989 dance drama film showcasing Gregory Hines’s tap-dancing talent alongside an ensemble of legendary hoofers.
  • 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: Tab
Triple: [Turk, givenName, Tab]
Generated description
Tab Turk is an individual whose given name is Tab, likely used as a personal or professional identifier.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tab
Target entity description: Tab Turk is an individual whose given name is Tab, likely used as a personal or professional identifier.
  • A. TAB
    TAB is the abbreviation for the United Nations Technical Assistance Board, a UN body historically responsible for coordinating technical aid and development assistance to member countries.
  • B. TAB
    TAB is the IATA airport code for A.N.R. Robinson International Airport, the main international gateway to the island of Tobago in Trinidad and Tobago.
  • C. TABS
    TABS is a membership organization that represents and supports college-preparatory boarding schools through advocacy, research, and professional development.
  • D. TABSO
    TABSO was the former national airline of Bulgaria that operated during the socialist era before being reorganized into Balkan Bulgarian Airlines.
  • E. Tap
    Tap is a 1989 dance drama film showcasing Gregory Hines’s tap-dancing talent alongside an ensemble of legendary hoofers.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90c9b3448190aec1608836a5e913 completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55269d8c81909592277741a93db6 completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd58216a8c8190b1fffcb670f15e16 completed May 8, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69fd589144b8819099aadef126b8728f completed May 8, 2026, 3:29 a.m.
Created at: April 10, 2026, 1:17 a.m.