Triple
T14279079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wood Street, Cardiff |
E353993
|
entity |
| Predicate | hasPostTown |
P2711
|
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: [Wood Street, Cardiff, hasPostTown, CARDIFF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CARDIFF Context triple: [Wood Street, Cardiff, hasPostTown, 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.
New Cardiff
New Cardiff is a romantic drama novel by British author Charles Webb that explores themes of love, identity, and reinvention through the story of a disillusioned Englishman who starts over in a small Canadian town.
-
C.
London–Cardiff
London–Cardiff is a major intercity travel corridor in the United Kingdom linking the capital city of London with the Welsh capital, Cardiff.
-
D.
Cardiff-by-the-Sea
Cardiff-by-the-Sea is a laid-back coastal community in northern San Diego County known for its beaches, surf culture, and small-town charm.
-
E.
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.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6585270c8190a717127b2f5dab3b |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c31654c81908f53d4c21e255afb |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:10 a.m.