Triple
T815937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swift (programming language) |
E17651
|
entity |
| Predicate | influencedBy |
P9
|
FINISHED |
| Object | CLU |
E96199
|
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: CLU | Statement: [Swift (programming language), influencedBy, CLU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLU Context triple: [Swift (programming language), influencedBy, CLU]
-
A.
CLU
chosen
CLU is an early high-level programming language from the 1970s that pioneered data abstraction, iterators, and exception handling, significantly influencing the design of later languages.
-
B.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
-
C.
UCLS
UCLS is a renowned private day school in Chicago affiliated with the University of Chicago, known for its progressive education and strong academic programs from nursery through high school.
-
D.
UCH
UCH is a leading public research university in Santiago, Chile, renowned for its academic excellence and significant influence on the country’s intellectual and cultural life.
-
E.
CLA
The Mercedes-Benz CLA is a compact luxury four-door coupé known for its sleek styling, advanced technology, and entry-level positioning within the brand’s lineup.
- 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_69a7928d2ee8819091dbef1dd5272f6f |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.