Triple
T13665995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yungang Grottoes |
E327121
|
entity |
| Predicate | distanceFromDatong |
P111061
|
FINISHED |
| Object | about 16 km west |
—
|
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: about 16 km west | Statement: [Yungang Grottoes, distanceFromDatong, about 16 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDatong Context triple: [Yungang Grottoes, distanceFromDatong, about 16 km west]
-
A.
distanceFromBeijing_km
Indicates the physical distance, measured in kilometers, between a given place or object and Beijing.
-
B.
distanceFromBeijingCityCenter
Indicates the physical distance between an entity’s location and the geographic center of Beijing city.
-
C.
distanceToDaNang_km
Indicates the distance, measured in kilometers, between a given location and Da Nang.
-
D.
distanceFromCaoBangCity
Indicates the measured distance between a given location and Cao Bang City.
-
E.
distanceFromChengdu
Indicates the measured spatial distance between a given location and the city of Chengdu.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc623fcc88190bbad97541c040b7a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.