Triple
T27486398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G85 Yinchuan–Kunming Expressway |
E693748
|
entity |
| Predicate | connectsProvincialCapital |
P105217
|
FINISHED |
| Object | Yinchuan |
—
|
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: Yinchuan | Statement: [G85 Yinchuan–Kunming Expressway, connectsProvincialCapital, Yinchuan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsProvincialCapital Context triple: [G85 Yinchuan–Kunming Expressway, connectsProvincialCapital, Yinchuan]
-
A.
regionCapitalConnected
Indicates that a capital city is directly connected (e.g., by transport or infrastructure) to its surrounding region.
-
B.
connectsCapitalOf
Indicates a relationship where one entity serves as the capital city of another entity, linking the capital to the political or administrative unit it represents.
-
C.
hasCountryCapitalConnection
Indicates a relationship in which a specific country is associated with its official capital city.
-
D.
connectsProvinceOrRegion
Indicates that one entity serves to link or provide a connection between a specific province or region and another entity.
-
E.
connectsCapitalsOf
chosen
Indicates a relationship where something serves as a link or route between the capital cities of two regions or countries.
- 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_69ef5382b9648190be0b1ef2ad5d043c |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 27, 2026, 1:02 p.m.