Triple
T19516993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huw Ceredig |
E488301
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Cardiff |
E12034
|
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: Cardiff | Statement: [Huw Ceredig, residence, Cardiff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cardiff Context triple: [Huw Ceredig, residence, Cardiff]
-
A.
Cardiff
chosen
Cardiff is the capital and largest city of Wales, known as a major cultural, commercial, and sporting center with a rich industrial and maritime history.
-
B.
Cardiff
Cardiff is an unincorporated community and census-designated place within Egg Harbor Township in Atlantic County, New Jersey, known primarily as a suburban residential area with local commercial development.
-
C.
Swansea
Swansea is a coastal city in South Wales known for its maritime heritage, industrial history, and role as a target during World War II air raids.
-
D.
Swansea
Swansea is a coastal town in Bristol County, Massachusetts, known for its suburban character and proximity to both Providence and Fall River.
-
E.
Glasgwm
Glasgwm is a mountain in southern Snowdonia, Wales, known for its rugged terrain and scenic views within the Aran range.
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359ca7648190804c4d655170fda3 |
completed | April 20, 2026, 2:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a074727002c8190aa3783c66242a4e4 |
completed | May 15, 2026, 4:17 p.m. |
Created at: April 10, 2026, 1:40 p.m.