Triple
T29919044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braunschweig Lion and castle ensemble on Burgplatz |
E759869
|
entity |
| Predicate | hasMaterialComponent |
P1845
|
FINISHED |
| Object | bronze sculpture |
—
|
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: bronze sculpture | Statement: [Braunschweig Lion and castle ensemble on Burgplatz, hasMaterialComponent, bronze sculpture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaterialComponent Context triple: [Braunschweig Lion and castle ensemble on Burgplatz, hasMaterialComponent, bronze sculpture]
-
A.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
B.
hasMaterialResource
Indicates that an entity possesses, controls, or has access to a tangible material resource.
-
C.
hasMaterialAspect
Indicates that something possesses a physical or tangible component or aspect as part of its overall nature or existence.
-
D.
hasMaterialOption
Indicates that an entity can be made from, or is available in, one or more alternative materials.
-
E.
hasMaterialRole
Indicates that an entity participates in an activity or context by fulfilling a specific material-related role or function.
- 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_69f2246189fc8190996b63ee1f9a2374 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69ff76ac40988190a34d858b5472ee2b |
completed | May 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69ff760a90948190a12fcb80e6e3e14b |
completed | May 9, 2026, 5:59 p.m. |
Created at: April 29, 2026, 6:13 p.m.