Triple
T38273774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | municipality of Santiago de Cuba |
E1021285
|
entity |
| Predicate | secondLargestUrbanAreaOf |
P2968
|
FINISHED |
| Object | Cuba |
E10524
|
NE 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: Cuba | Statement: [municipality of Santiago de Cuba, secondLargestUrbanAreaOf, Cuba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondLargestUrbanAreaOf Context triple: [municipality of Santiago de Cuba, secondLargestUrbanAreaOf, Cuba]
-
A.
secondLargestMetropolitanArea
Indicates that one entity is the second largest metropolitan area (by population or size, as context defines) within the scope defined by the other entity.
-
B.
isSecondMostPopulousCityIn
chosen
Indicates that a city is the second most populous city within a specified larger region or country.
-
C.
secondLargestTownIn
Indicates that one town is the second largest town (by size or population) within a specified region or administrative area.
-
D.
secondMetropolitan
Indicates that one entity is the second metropolitan (e.g., second-ranking or second-designated metropolitan authority or see) in relation to another entity.
-
E.
secondLargestUNCentreAfter
Indicates that one entity is the second-largest United Nations centre following another specified UN centre in terms of size or importance.
- F. None of above.
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_69f76dee198c8190bf5109421e47a658 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffde9263248190996f970b6cf6e49d |
completed | May 10, 2026, 1:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4193b941c88190a74601c6a89aec62 |
completed | June 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69ffdd760f1c8190abc6c0c1cd97ba5f |
completed | May 10, 2026, 1:20 a.m. |
Created at: May 3, 2026, 4:30 p.m.