Triple
T10804455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mataró |
E254926
|
entity |
| Predicate | hasPopulationRankingInMaresme |
P61465
|
FINISHED |
| Object | largest city in Maresme |
—
|
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 Maresme | Statement: [Mataró, hasPopulationRankingInMaresme, largest city in Maresme]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankingInMaresme Context triple: [Mataró, hasPopulationRankingInMaresme, largest city in Maresme]
-
A.
populationRankInValencianCommunity
Indicates the relative position of an entity in terms of population size compared to other entities within the Valencian Community.
-
B.
hasPopulationRankInDepartment
Indicates the relative position of an entity’s population size compared to other entities within the same department.
-
C.
populationRankInCommunityOfMadrid
Indicates the relative position of an entity in terms of population size compared to other entities within the Community of Madrid.
-
D.
isMostPopulousMunicipalityOf
chosen
Indicates that a municipality has the largest population among all municipalities within the specified administrative area or region.
-
E.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73370e7388190885b104fc883456e |
completed | April 9, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:18 p.m.