Triple
T25287209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bulawayo Province |
E633973
|
entity |
| Predicate | hasRankInCountryByCitySize |
P69297
|
FINISHED |
| Object | second-largest city center |
—
|
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: second-largest city center | Statement: [Bulawayo Province, hasRankInCountryByCitySize, second-largest city center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankInCountryByCitySize Context triple: [Bulawayo Province, hasRankInCountryByCitySize, second-largest city center]
-
A.
hasCityRank
chosen
Indicates that a city holds a particular rank or position within a defined ordering or hierarchy (such as size, importance, or administrative level).
-
B.
isGlobalCityRank
Indicates the relative position or ranking of a city within a global hierarchy of cities based on specified criteria.
-
C.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
capacityRankInWorld
Indicates the relative position or ranking of an entity’s capacity compared to all similar entities worldwide.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48e09f11481908c65718e522a3e02 |
completed | May 1, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 1:19 p.m.