Triple
T11825758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universal Credit |
E281256
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | UC |
E281256
|
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: UC | Statement: [Universal Credit, shortName, UC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UC Context triple: [Universal Credit, shortName, UC]
-
A.
UC
UC is a public university in Canberra, Australia, known for its career-focused programs and strong industry partnerships.
-
B.
UC
UC is a leading Chilean university, widely recognized for its academic excellence and strong influence in education, research, and public policy in Latin America.
-
C.
UC
UC is the final generation of the Holden Torana, a compact Australian car produced in the late 1970s.
-
D.
UC
chosen
UC is the commonly used abbreviation for Universal Credit, the United Kingdom’s main welfare benefit for people on a low income or out of work.
-
E.
UC
UC is a public research university in Cincinnati, Ohio, known for its comprehensive academic programs and co-operative education opportunities.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5eb299481909de3c0e85628fbe4 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f132062b108190ad33656c386ee603 |
completed | April 28, 2026, 10:17 p.m. |
Created at: April 8, 2026, 9:43 p.m.