Triple
T3060736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Heroes |
E60589
|
entity |
| Predicate | cityRankByPopulationInIndonesia |
P23005
|
FINISHED |
| Object | second-largest city |
—
|
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 | Statement: [City of Heroes, cityRankByPopulationInIndonesia, second-largest city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityRankByPopulationInIndonesia Context triple: [City of Heroes, cityRankByPopulationInIndonesia, second-largest city]
-
A.
populationRankInIndonesia
chosen
Indicates the relative position of an entity in terms of population size compared to other entities within Indonesia.
-
B.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
cityPopulationContext
Indicates the contextual relationship between a city and information about its population, such as size, distribution, or demographic characteristics.
-
D.
countryPopulationContext
Indicates the contextual population characteristics or statistics associated with a specific country.
-
E.
hasPopulationOver
Indicates that one entity has a population greater than a specified number or than another 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e9e1e248190b5ed5ebcdad1321e |
completed | March 8, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.