Triple
T17674390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craig Schaffert |
E440607
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | CLU |
—
|
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: CLU | Statement: [Craig Schaffert, notableWork, CLU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLU Context triple: [Craig Schaffert, notableWork, 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.
CLU
CLU is a private liberal arts university in Thousand Oaks, California, known for its programs in business, education, and the humanities within a Lutheran tradition.
-
C.
CU
CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
-
D.
CU
CU is the station code used to identify Cubao station on Manila’s MRT Line 3.
-
E.
CU
CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6ba22081909e2099490c047378 |
completed | April 19, 2026, 6 a.m. |
Created at: April 10, 2026, 10 a.m.