Triple
T19111892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TLA+ |
E467809
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | TLA+ Toolbox |
—
|
NE NERFINISHED |
How this triple was built (2 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: TLA+ Toolbox | Statement: [TLA+, hasComponent, TLA+ Toolbox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TLA+ Toolbox Context triple: [TLA+, hasComponent, TLA+ Toolbox]
-
A.
TLA+ Toolbox
chosen
TLA+ Toolbox is an integrated development environment for writing, editing, and model-checking TLA+ specifications and PlusCal algorithms.
-
B.
TLA+
TLA+ is a formal specification language developed by Leslie Lamport for modeling and verifying concurrent and distributed systems using mathematical logic.
-
C.
TLA+ proof system
The TLA+ proof system is a formal verification framework that allows users to mechanically check the correctness of TLA+ specifications using machine-checked logical proofs.
-
D.
TLA+ model checker TLC
TLA+ model checker TLC is an automated verification tool that exhaustively explores the state space of TLA+ specifications to detect errors such as deadlocks, invariant violations, and liveness issues.
-
E.
TLC model checker
The TLC model checker is a tool for exhaustively verifying TLA+ specifications by exploring all possible system behaviors to detect errors such as deadlocks and invariant violations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e394969c81909d09b2300ea0e041 |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:04 p.m.