Triple

T37044164
Position Surface form Disambiguated ID Type / Status
Subject Puerto Nuevo Beach E916860 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Puerto Nuevo barrio
Puerto Nuevo barrio is a coastal neighborhood in Vega Baja, Puerto Rico, known for its proximity to the popular Puerto Nuevo Beach and its scenic oceanfront setting.
E2210565 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: Puerto Nuevo barrio | Statement: [Puerto Nuevo Beach, hasNearbySettlement, Puerto Nuevo barrio]
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: Puerto Nuevo barrio
Triple: [Puerto Nuevo Beach, hasNearbySettlement, Puerto Nuevo barrio]
Generated description
Puerto Nuevo barrio is a coastal neighborhood in Vega Baja, Puerto Rico, known for its proximity to the popular Puerto Nuevo Beach and its scenic oceanfront setting.

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_69f76e93ec4c8190be81cf87354d9155 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fa01299f548190bca57149345b07c3 completed May 5, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c45ee9c8190ba73578ca290f1e4 completed June 26, 2026, 2:27 p.m.
NEDg Description generation batch_6a3e9c5e5aa48190a0a24c68604d55c4 completed June 26, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a3ea4f5a89081908e33f3dae0c103c3 completed June 26, 2026, 4:12 p.m.
Created at: May 3, 2026, 4:14 p.m.