Triple
T18528507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rasmus Lerdorf |
E452777
|
entity |
| Predicate | influencedBy |
P9
|
FINISHED |
| Object | C programming language |
—
|
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 programming language | Statement: [Rasmus Lerdorf, influencedBy, C programming language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: C programming language Context triple: [Rasmus Lerdorf, influencedBy, C programming language]
-
A.
The C Programming Language
The C Programming Language is a classic programming book that introduced and defined the C language, serving as its authoritative reference and a foundational text in computer science.
-
B.
C
C is a local service on the New York City Subway that runs along the Eighth Avenue Line in Manhattan and continues through Brooklyn.
-
C.
C
C is a light rail service designation used by the Los Angeles Metro system for one of its primary rail lines.
-
D.
C
C is a tram route designation used in the Strasbourg tramway network in France.
-
E.
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.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e533fad2d081908395914d6a6b4eb1 |
completed | April 19, 2026, 7:58 p.m. |
Created at: April 10, 2026, 11:37 a.m.