Triple
T7116752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Bertha howitzer |
E165838
|
entity |
| Predicate | materialEffect |
P74644
|
FINISHED |
| Object | demolition of concrete fortifications |
—
|
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: demolition of concrete fortifications | Statement: [Big Bertha howitzer, materialEffect, demolition of concrete fortifications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialEffect Context triple: [Big Bertha howitzer, materialEffect, demolition of concrete fortifications]
-
A.
materialParameter
Indicates a relationship where a specific parameter or property is associated with, or characterizes, a material in a given context.
-
B.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
C.
materialDepicted
Indicates that a work or representation visually portrays or includes a particular material as part of its subject.
-
D.
exampleMaterial
Indicates that something serves as a representative or illustrative material or sample of something else.
-
E.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e617a528819085d4b8e1b5699966 |
completed | March 27, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e456e89481908df42a1b4232a4a0 |
completed | March 27, 2026, 8:11 p.m. |
Created at: March 27, 2026, 2:43 p.m.