Triple
T22489600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Io (programming language) |
E555977
|
entity |
| Predicate | implementationLanguage |
P18654
|
FINISHED |
| Object | C |
—
|
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: C | Statement: [Io (programming language), implementationLanguage, C]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: C Context triple: [Io (programming language), implementationLanguage, 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.
C
C is the New York Stock Exchange ticker symbol for Citigroup Inc., a major global financial services and banking corporation.
-
C.
C
C is one of the three central women in Edward Albee’s play "Three Tall Women," representing a younger stage of the protagonist’s life and perspective.
-
D.
C
C is a Copenhagen S-train commuter rail line that runs through central Copenhagen and connects key suburban areas in the metropolitan network.
-
E.
C
C is a tram route designation used in the Strasbourg tramway network in France.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3f3b4c819092bfe6495c61db46 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.