Triple
T4707669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argus |
E104429
|
entity |
| Predicate | basedOn |
P98
|
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: [Argus, basedOn, CLU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLU Context triple: [Argus, basedOn, 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 common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
-
C.
CU
CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
-
D.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
-
E.
CLY
CLY is the IATA airport code for Calvi – Sainte-Catherine Airport, a regional airport serving the town of Calvi on the island of Corsica, France.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63ebf7e48190b545670ec114bd7e |
completed | March 20, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be106d1fc08190808c19025c6f37c4 |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:17 p.m.