Triple
T3906631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwen Cooper |
E87216
|
entity |
| Predicate | countryOfFictionalOrigin |
P26
|
FINISHED |
| Object | Wales |
E9984
|
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: Wales | Statement: [Gwen Cooper, countryOfFictionalOrigin, Wales]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wales Context triple: [Gwen Cooper, countryOfFictionalOrigin, Wales]
-
A.
Wales
chosen
Wales is a country on the western side of Great Britain, known for its distinct Celtic culture, Welsh language, mountainous national parks, and historic castles.
-
B.
Talywain
Talywain is a small village and former coal-mining community in the county borough of Torfaen in south-east Wales.
-
C.
Morgannwg
Morgannwg is the traditional Welsh name for the historic county of Glamorgan in south Wales, known for its rich medieval heritage and early industrial development.
-
D.
England and Wales
England and Wales is a legal jurisdiction within the United Kingdom, encompassing two of its constituent countries and sharing a unified legal system and many governmental institutions.
-
E.
England
England is a country within the United Kingdom, known for its rich history, cultural influence, and major cities such as London and Manchester.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed1290e48190aaf2d8b2a7be707a |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5285093208190a2ba00afcbd8a261 |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:22 p.m.