Triple

T36658495
Position Surface form Disambiguated ID Type / Status
Subject City of Havana metropolitan area E905055 entity
Predicate containsMunicipality P852 FINISHED
Object Habana del Este
Habana del Este is a coastal municipality on the eastern side of Havana, Cuba, known for its residential neighborhoods and popular beaches such as Santa María del Mar.
E2200114 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: Habana del Este | Statement: [City of Havana metropolitan area, containsMunicipality, Habana del Este]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Habana del Este
Triple: [City of Havana metropolitan area, containsMunicipality, Habana del Este]
Generated description
Habana del Este is a coastal municipality on the eastern side of Havana, Cuba, known for its residential neighborhoods and popular beaches such as Santa María del Mar.

Provenance (5 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_69f76e6e3b908190970251b30f76ad71 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c77a12fc8190b309606d38a8e145 completed May 3, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dde4bffb88190a29108fde251ce58 completed June 26, 2026, 2:05 a.m.
NEDg Description generation batch_6a3ddf3854988190b4751513b286cbf8 completed June 26, 2026, 2:08 a.m.
NED2 Entity disambiguation (via description) batch_6a3de10d28a081908c8082d642f1275d completed June 26, 2026, 2:16 a.m.
Created at: May 3, 2026, 4:11 p.m.