Triple

T816969
Position Surface form Disambiguated ID Type / Status
Subject PostgreSQL E17669 entity
Predicate supportsLanguage P2177 FINISHED
Object PL/Tcl
PL/Tcl is a procedural language extension for PostgreSQL that allows writing database functions and triggers using the Tcl scripting language.
E97111 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: PL/Tcl | Statement: [PostgreSQL, supportsLanguage, PL/Tcl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PL/Tcl
Context triple: [PostgreSQL, supportsLanguage, PL/Tcl]
  • A. PDL
    PDL is a former name for USL League Two, a North American pre-professional soccer league that serves as a key development platform for college-aged and aspiring professional players.
  • B. SETL
    SETL is a high-level programming language developed in the late 1960s that is notable for its powerful set-theoretic abstractions and influence on later language design.
  • C. TXL
    TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
  • D. Pascal
    Pascal is a high-level, strongly typed procedural programming language designed by Niklaus Wirth in the late 1960s, widely used for teaching structured programming and data structuring concepts.
  • E. PTC
    PTC is an advanced safety system used on railroads to automatically prevent train collisions, overspeed derailments, and other dangerous movements.
  • 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: PL/Tcl
Triple: [PostgreSQL, supportsLanguage, PL/Tcl]
Generated description
PL/Tcl is a procedural language extension for PostgreSQL that allows writing database functions and triggers using the Tcl scripting language.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PL/Tcl
Target entity description: PL/Tcl is a procedural language extension for PostgreSQL that allows writing database functions and triggers using the Tcl scripting language.
  • A. PDL
    PDL is a former name for USL League Two, a North American pre-professional soccer league that serves as a key development platform for college-aged and aspiring professional players.
  • B. SETL
    SETL is a high-level programming language developed in the late 1960s that is notable for its powerful set-theoretic abstractions and influence on later language design.
  • C. TXL
    TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
  • D. Pascal
    Pascal is a high-level, strongly typed procedural programming language designed by Niklaus Wirth in the late 1960s, widely used for teaching structured programming and data structuring concepts.
  • E. PTC
    PTC is an advanced safety system used on railroads to automatically prevent train collisions, overspeed derailments, and other dangerous movements.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a78bd0a1d48190907434a17853dfb1 completed March 4, 2026, 1:33 a.m.
NED2 Entity disambiguation (via description) batch_69a78c3a57d88190a994ed44bcb2d8d1 completed March 4, 2026, 1:34 a.m.
Created at: March 1, 2026, 7:38 p.m.