Triple
T13341648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Nanyuan area |
E317840
|
entity |
| Predicate | directionRelativeToBeijingCenter |
P28261
|
FINISHED |
| Object | south |
—
|
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: south | Statement: [Beijing Nanyuan area, directionRelativeToBeijingCenter, south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: directionRelativeToBeijingCenter Context triple: [Beijing Nanyuan area, directionRelativeToBeijingCenter, south]
-
A.
distanceFromBeijingCityCenter
Indicates the physical distance between an entity’s location and the geographic center of Beijing city.
-
B.
directionFromEarth
Indicates the compass or spatial direction in which an entity is located as observed from Earth.
-
C.
directionFromCityCenter
chosen
Indicates the compass direction in which one location lies relative to the city center.
-
D.
distanceFromCityCenterDirection
Indicates the distance and compass direction of a location relative to the center of a specified city.
-
E.
geographicDirectionWithinCountry
Indicates that one place lies in a specified cardinal or intercardinal direction relative to another place within the same country.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d0379d481909a50fff31b19fed1 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:31 p.m.