Triple
T23721832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China and North Korea |
E586165
|
entity |
| Predicate | ChineseCapital |
P35753
|
FINISHED |
| Object | Beijing |
—
|
NE NERFINISHED |
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: Beijing | Statement: [China and North Korea, ChineseCapital, Beijing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ChineseCapital Context triple: [China and North Korea, ChineseCapital, Beijing]
-
A.
hostsCapitalOf
Indicates that one location serves as the capital city of another administrative or political entity.
-
B.
cityAsCapitalOf
chosen
Indicates that a city serves as the official capital of a specified political or administrative entity.
-
C.
lostCapital
Indicates that an entity has ceased to be the capital of a political or administrative region.
-
D.
raceCapitalOf
Indicates that the subject city is the primary center or capital for a particular race-related activity, event, or community.
-
E.
capitalAreaOf
Indicates that a specified area value represents the total land or geographic size of the capital city of a given entity.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b91177c08190bea6e62ed13e2495 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:02 p.m.