Triple
T16605420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gravelines |
E403436
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Dunkirk |
E33602
|
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: Dunkirk | Statement: [Gravelines, near, Dunkirk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dunkirk Context triple: [Gravelines, near, Dunkirk]
-
A.
Dunkirk
Dunkirk is a 2017 war film directed by Christopher Nolan that depicts the World War II evacuation of Allied soldiers from the beaches of Dunkirk, France.
-
B.
Dunkirk
chosen
Dunkirk is a coastal town in northern France best known as the site of the World War II evacuation of Allied troops in 1940.
-
C.
Dunkirk
Dunkirk is a small rural civil parish and village in the county of Kent in southeast England.
-
D.
Darkest Hour
Darkest Hour is a 2017 historical drama film depicting Winston Churchill’s early days as British Prime Minister during World War II, starring Gary Oldman in an Oscar-winning performance.
-
E.
Darkest Hour
Darkest Hour is an American metal band known for blending melodic death metal and hardcore punk influences into an aggressive, politically charged sound.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36090cf388190b401c55230912104 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0075a8a6248190a9e2bb469d821c66 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:17 a.m.