Triple
T13976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D-Day |
E280
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Normandy |
E861
|
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: Normandy | Statement: [D-Day, location, Normandy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Normandy Context triple: [D-Day, location, Normandy]
-
A.
Vichy
Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
-
B.
France
chosen
France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
-
C.
Belgium
Belgium is a Western European country known for its role as a founding member of major international organizations, including NATO and the European Union, and for hosting many of their key institutions.
-
D.
Paris
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
-
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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a240014418819090625e2fb774a2e6 |
completed | Feb. 28, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2552c22f88190afcc8ed45c419844 |
completed | Feb. 28, 2026, 2:38 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.