Triple
T2861958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Goodwood |
E63341
|
entity |
| Predicate | opposingForceType |
P31619
|
FINISHED |
| Object | German armoured and infantry divisions |
—
|
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: German armoured and infantry divisions | Statement: [Operation Goodwood, opposingForceType, German armoured and infantry divisions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposingForceType Context triple: [Operation Goodwood, opposingForceType, German armoured and infantry divisions]
-
A.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
-
B.
typeOfOpposition
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
C.
opposingForcesStatus
Indicates the current state or condition of two or more forces that are in conflict or opposition to each other.
-
D.
hasOpposingForceType
chosen
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
-
E.
opposedWar
Indicates that an entity actively resisted, disagreed with, or worked against a particular war or military conflict.
- F. None of above.
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_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. |
Created at: March 6, 2026, 10:02 p.m.