Triple
T19515381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsar Cannon |
E488263
|
entity |
| Predicate | cannonballsFunction |
P136201
|
FINISHED |
| Object | purely decorative |
—
|
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: purely decorative | Statement: [Tsar Cannon, cannonballsFunction, purely decorative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cannonballsFunction Context triple: [Tsar Cannon, cannonballsFunction, purely decorative]
-
A.
numberOfCanons
Indicates the quantity of canons associated with or possessed by a given entity.
-
B.
hasCannon
Indicates that one entity is equipped with, contains, or features a cannon.
-
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.
courseOfFire
Indicates the specific sequence, arrangement, and conditions of shots or stages that define how a shooting exercise or match is to be conducted.
-
E.
numberOfCatapults
Indicates the quantity of catapults associated with a given entity or context.
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359b90f08190b38359dc9e97e11c |
completed | April 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.