Triple
T10533961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skala de la Ville |
E248514
|
entity |
| Predicate | hasCannonMaterial |
P1845
|
FINISHED |
| Object | bronze |
—
|
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 | Statement: [Skala de la Ville, hasCannonMaterial, bronze]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCannonMaterial Context triple: [Skala de la Ville, hasCannonMaterial, bronze]
-
A.
hasHornMaterial
Indicates that an entity’s horn is made of, or composed from, a specified material.
-
B.
hasLanternMaterial
Indicates that an entity’s lantern is made from or composed of a specified material.
-
C.
usesCanons
Indicates that one entity employs or makes use of canons (such as rules, principles, or artillery pieces) in relation to another entity or context.
-
D.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
E.
hasMaterialOption
Indicates that an entity can be made from, or is available in, one or more alternative materials.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a1a754c8190b53f2df28a1dfef1 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb9729288190a0149f127acd7ae3 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:31 p.m.