Triple
T15081757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byodo-In Temple |
E360162
|
entity |
| Predicate | hasBellWeight |
P117237
|
FINISHED |
| Object | approximately 3 tons |
—
|
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 3 tons | Statement: [Byodo-In Temple, hasBellWeight, approximately 3 tons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBellWeight Context triple: [Byodo-In Temple, hasBellWeight, approximately 3 tons]
-
A.
hasBells
Indicates that an entity possesses or is equipped with one or more bells.
-
B.
bellsUsedFor
Indicates that certain bells are employed or utilized for a particular purpose, function, or activity.
-
C.
numberOfBells
Indicates the quantity of bells associated with or present in a given entity or context.
-
D.
hasHeavierSoundThan
Indicates that one entity produces or is associated with a sound that is sonically heavier, more intense, or more forceful than that of another entity.
-
E.
isLargestBellOf
Indicates that one bell is the largest bell belonging to, or associated with, a particular entity or collection.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027450a48190a84588b6aaf84ebf |
completed | April 15, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:03 a.m.