Triple
T31556153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryongsong Residence |
E805132
|
entity |
| Predicate | distanceFromPyongyangCenter |
P150524
|
FINISHED |
| Object | approximately 12 km (reported) |
—
|
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 12 km (reported) | Statement: [Ryongsong Residence, distanceFromPyongyangCenter, approximately 12 km (reported)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPyongyangCenter Context triple: [Ryongsong Residence, distanceFromPyongyangCenter, approximately 12 km (reported)]
-
A.
distanceFromPyongyang
chosen
Indicates the measured spatial distance between a given location and the city of Pyongyang.
-
B.
distanceFromApia
Indicates the measured distance between a given location and Apia.
-
C.
distanceFromPyeongchangOlympicPlaza
Indicates the measured distance between a given place or object and the Pyeongchang Olympic Plaza.
-
D.
distanceFromBeijingCityCenter
Indicates the physical distance between an entity’s location and the geographic center of Beijing city.
-
E.
distanceToSeoul
Indicates the measured or estimated spatial distance between a given entity’s location and the city of Seoul.
- 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_69f348d22e088190ad555d5bd42f9da0 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a01d7b3ce8c8190b2f90be730505765 |
completed | May 11, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_6a01d5115a6c8190a6d9f96ec484135a |
completed | May 11, 2026, 1:09 p.m. |
Created at: April 30, 2026, 10:13 p.m.