Triple
T15498560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple 69: Kannonji |
E378887
|
entity |
| Predicate | hasNumberWithinRoute |
P34375
|
FINISHED |
| Object | 69 of 88 |
—
|
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: 69 of 88 | Statement: [Temple 69: Kannonji, hasNumberWithinRoute, 69 of 88]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberWithinRoute Context triple: [Temple 69: Kannonji, hasNumberWithinRoute, 69 of 88]
-
A.
isNumberedRouteIn
Indicates that a numbered route (such as a highway or road with an assigned number) is located within or passes through a specified geographic or administrative area.
-
B.
hasRouteNumberingScheme
Indicates that one entity uses or is assigned a particular system or scheme for numbering its routes.
-
C.
hasNumberInStructure
Indicates that an entity’s structure includes or contains a specific numerical value or component.
-
D.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
E.
hasRouteIdentifier
chosen
Indicates that an entity is associated with a specific route code or identifier used to distinguish it from other routes.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fb0aee081909db1c54349ec8492 |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:53 a.m.