Triple
T3788094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simatai section |
E85576
|
entity |
| Predicate | distanceFromBeijingUrbanCenter |
P48910
|
FINISHED |
| Object | approximately 120 kilometers northeast |
—
|
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 120 kilometers northeast | Statement: [Simatai section, distanceFromBeijingUrbanCenter, approximately 120 kilometers northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBeijingUrbanCenter Context triple: [Simatai section, distanceFromBeijingUrbanCenter, approximately 120 kilometers northeast]
-
A.
distanceFromBeijingCityCenter
chosen
Indicates the physical distance between an entity’s location and the geographic center of Beijing city.
-
B.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
C.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
D.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
E.
directionFromCityCenter
Indicates the compass direction in which one location lies relative to the city center.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d4bc3c81909bd56e33d43fa8e4 |
completed | March 9, 2026, 3:14 p.m. |
Created at: March 9, 2026, 3:13 p.m.