Triple
T14002453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Changzhi |
E336861
|
entity |
| Predicate | populationRankInShanxi |
P112108
|
FINISHED |
| Object | among larger cities of Shanxi |
—
|
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: among larger cities of Shanxi | Statement: [Changzhi, populationRankInShanxi, among larger cities of Shanxi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInShanxi Context triple: [Changzhi, populationRankInShanxi, among larger cities of Shanxi]
-
A.
populationRankInLiaoning
Indicates the relative position of an entity in terms of population size compared to other entities within Liaoning province.
-
B.
populationRankInQinghai
Indicates the relative position of an entity in a ranking ordered by population size within Qinghai.
-
C.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
D.
provinceRank
Indicates the relative position or level assigned to a province within an ordered ranking or hierarchy.
-
E.
populationRankInVirginia
Indicates the relative position of an entity in terms of population size compared to other entities within Virginia.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed06a50819093ddc64f55050689 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:19 p.m.