Triple
T10311039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xining |
E241888
|
entity |
| Predicate | populationRankInQinghai |
P93310
|
FINISHED |
| Object | largest city in Qinghai |
—
|
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: largest city in Qinghai | Statement: [Xining, populationRankInQinghai, largest city in Qinghai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInQinghai Context triple: [Xining, populationRankInQinghai, largest city in Qinghai]
-
A.
populationRankInLiaoning
Indicates the relative position of an entity in terms of population size compared to other entities within Liaoning province.
-
B.
rankInChinaByArea
Indicates the position of an entity in an ordered list of entities in China when sorted by their area size.
-
C.
provinceRank
Indicates the relative position or level assigned to a province within an ordered ranking or hierarchy.
-
D.
populationRankInQueensland
Indicates the relative position of an entity in terms of population size compared to other entities within Queensland.
-
E.
populationRankAfter
Indicates the relative position of an entity in a population-based ordering that comes after another entity’s population rank.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:47 a.m.