Triple
T2861820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VIII Corps (United Kingdom) |
E63338
|
entity |
| Predicate | notableObjectiveInNormandy |
P42767
|
FINISHED |
| Object | breakout from Caen sector |
—
|
LITERAL 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: breakout from Caen sector | Statement: [VIII Corps (United Kingdom), notableObjectiveInNormandy, breakout from Caen sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableObjectiveInNormandy Context triple: [VIII Corps (United Kingdom), notableObjectiveInNormandy, breakout from Caen sector]
-
A.
objectiveOfFrance
Indicates that something is an objective, goal, or aim pursued by France.
-
B.
roleAtNormandy
Indicates the specific role, position, or function an entity held in the context of the Normandy event or setting.
-
C.
numberOfChannelCrossingsAtNormandy
Indicates the number of times an entity crossed the English Channel specifically in relation to the Normandy area or campaign.
-
D.
objectiveInArdennes
Indicates that an entity has an objective, mission, or goal located in or pertaining to the Ardennes region.
-
E.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
- F. None of above. chosen
Provenance (4 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf8df8288190816767169ea7cbf9 |
completed | March 7, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddedd72c819094a9c4161af07780 |
completed | March 7, 2026, 8:12 a.m. |
Created at: March 6, 2026, 10:02 p.m.