Triple
T19515312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsar Bell |
E488262
|
entity |
| Predicate | weightClaim |
P136196
|
FINISHED |
| Object | largest bell ever cast |
—
|
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: largest bell ever cast | Statement: [Tsar Bell, weightClaim, largest bell ever cast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weightClaim Context triple: [Tsar Bell, weightClaim, largest bell ever cast]
-
A.
weightIssue
Indicates that there is a problem, concern, or abnormal condition related to the weight of an entity.
-
B.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
C.
weightSupport
Indicates that one entity bears or carries the physical weight of another, providing structural or mechanical support.
-
D.
وزن
Indicates a relationship where one entity has, measures, or is characterized by a certain weight or mass.
-
E.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
- 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.