Triple
T33646896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sigismund Bell |
E861983
|
entity |
| Predicate | hasClapperWeight |
P117237
|
FINISHED |
| Object | approximately 350 kilograms |
—
|
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: approximately 350 kilograms | Statement: [Sigismund Bell, hasClapperWeight, approximately 350 kilograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClapperWeight Context triple: [Sigismund Bell, hasClapperWeight, approximately 350 kilograms]
-
A.
hasBellWeight
chosen
Indicates that an entity (typically a bell) has a specific weight value associated with it.
-
B.
hasCounterweightType
Indicates that an entity is associated with or uses a specific type or category of counterweight.
-
C.
hasRopeWeight
Indicates that an entity is associated with a specific rope weight used for it or by it.
-
D.
hasClasps
Indicates that one entity is equipped with or features clasps that fasten, secure, or attach it to another entity or its parts.
-
E.
isHeavierThan
Indicates that one entity has greater weight or mass than another entity.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 1, 2026, 1:42 a.m.