Triple
T32619836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle at the Ramelle bridge |
E833890
|
entity |
| Predicate | involvesVehicle |
P178671
|
FINISHED |
| Object | German Tiger tank |
—
|
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 Tiger tank | Statement: [Battle at the Ramelle bridge, involvesVehicle, German Tiger tank]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesVehicle Context triple: [Battle at the Ramelle bridge, involvesVehicle, German Tiger tank]
-
A.
utilityInvolved
Indicates that a utility service or provider is involved in, associated with, or plays a role in the referenced situation or relationship.
-
B.
occursInVehicle
Indicates that an event or action takes place within or on a vehicle.
-
C.
wasKeyVehicleIn
Indicates that a vehicle played a central or decisive role in a specified event, situation, or outcome.
-
D.
vehicleInScene
chosen
Indicates that a vehicle is present or appears within a particular scene.
-
E.
depictsVehicle
Indicates that one entity visually represents or portrays a vehicle in an image, artwork, or other depiction.
- 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_69f3492ccc80819086ef7d26e9786647 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 1, 2026, 1:06 a.m.