Triple
T2863800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miho Museum |
E63387
|
entity |
| Predicate | distanceFromKyoto |
P42797
|
FINISHED |
| Object | approximately 60 kilometers southeast of Kyoto |
—
|
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 60 kilometers southeast of Kyoto | Statement: [Miho Museum, distanceFromKyoto, approximately 60 kilometers southeast of Kyoto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKyoto Context triple: [Miho Museum, distanceFromKyoto, approximately 60 kilometers southeast of Kyoto]
-
A.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
B.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
C.
distanceFromGori
Indicates the spatial distance between a given entity or location and the place named Gori.
-
D.
distanceToSeattle
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
-
E.
distanceToJakarta_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Jakarta.
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfb853908190aa2fd492e9fa5e87 |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddedd72c819094a9c4161af07780 |
completed | March 7, 2026, 8:12 a.m. |
Created at: March 6, 2026, 10:02 p.m.