Triple

T3061210
Position Surface form Disambiguated ID Type / Status
Subject Visual Component Library E61999 entity
Predicate includes P1393 FINISHED
Object TTable
TTable is a Delphi VCL data-access component that represents and manipulates an entire database table through a live, table-based dataset interface.
 E322642 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: TTable | Statement: [Visual Component Library, includes, TTable]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TTable
Context triple: [Visual Component Library, includes, TTable]
  • A. Tababela
    Tababela is a rural parish in the Quito Metropolitan District of Ecuador, known for hosting the city’s main air gateway, Mariscal Sucre International Airport.
  • B. TBL
    TBL is the standard NHL abbreviation for the Tampa Bay Lightning professional ice hockey team.
  • C. Tabularium
    The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
  • D. The Table
    "The Table" is the English name of Surah Al-Ma'idah, a chapter of the Qur'an that addresses themes of lawful and unlawful food, covenants, and adherence to divine law.
  • E. Tisch
    Tisch is a surname most prominently associated with the American Tisch family, known for their influence in business, philanthropy, and the entertainment industry.
  • 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: TTable
Triple: [Visual Component Library, includes, TTable]
Generated description
TTable is a Delphi VCL data-access component that represents and manipulates an entire database table through a live, table-based dataset interface.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TTable
Target entity description: TTable is a Delphi VCL data-access component that represents and manipulates an entire database table through a live, table-based dataset interface.
  • A. Tababela
    Tababela is a rural parish in the Quito Metropolitan District of Ecuador, known for hosting the city’s main air gateway, Mariscal Sucre International Airport.
  • B. TBL
    TBL is the standard NHL abbreviation for the Tampa Bay Lightning professional ice hockey team.
  • C. Tabularium
    The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
  • D. The Table
    "The Table" is the English name of Surah Al-Ma'idah, a chapter of the Qur'an that addresses themes of lawful and unlawful food, covenants, and adherence to divine law.
  • E. Tisch
    Tisch is a surname most prominently associated with the American Tisch family, known for their influence in business, philanthropy, and the entertainment industry.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9e1e248190b5ed5ebcdad1321e completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef0e757481908eb1d9693474c49d completed March 11, 2026, 10:39 p.m.
NEDg Description generation batch_69b1efedc68481908c2fece012621f1f completed March 11, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69b1f07505c881909841f184af3e4319 completed March 11, 2026, 10:45 p.m.
Created at: March 8, 2026, 3:02 p.m.