Triple
T816226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stackless Python |
E17656
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | C |
E9269
|
NE FINISHED |
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: C | Statement: [Stackless Python, programmingLanguage, C]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: C Context triple: [Stackless Python, programmingLanguage, C]
-
A.
C
chosen
C is a foundational, general-purpose programming language known for its efficiency, low-level memory access, and influence on many later languages such as C++, Java, and Python.
-
B.
Terminal C
Terminal C is one of the main passenger terminals at Luis Muñoz Marín International Airport in Puerto Rico, serving commercial airline operations and traveler services.
-
C.
Terminal C
Terminal C is one of the main passenger terminals at New York City's LaGuardia Airport, serving numerous domestic flights and airlines.
-
D.
Terminal C
Terminal C is one of the passenger terminals at Dallas/Fort Worth International Airport, serving various domestic flights and airlines within the airport’s complex.
-
E.
Terminal C
Terminal C is a major passenger terminal at Newark Liberty International Airport, primarily serving United Airlines and offering extensive domestic and international flight operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4ab5157b08190b6c8f2fd455f261e |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c7103a00819087ad711a2ab99770 |
completed | March 4, 2026, 5:45 a.m. |
Created at: March 1, 2026, 7:38 p.m.