Triple

T37332237
Position Surface form Disambiguated ID Type / Status
Subject Port Salerno, Florida E926784 entity
Predicate hasNeighborhood P40 FINISHED
Object Manatee Pocket waterfront area
Manatee Pocket waterfront area is a scenic harbor and marina district in Port Salerno, Florida, known for its boating, fishing, and waterfront dining.
E2222957 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: Manatee Pocket waterfront area | Statement: [Port Salerno, Florida, hasNeighborhood, Manatee Pocket waterfront area]
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: Manatee Pocket waterfront area
Triple: [Port Salerno, Florida, hasNeighborhood, Manatee Pocket waterfront area]
Generated description
Manatee Pocket waterfront area is a scenic harbor and marina district in Port Salerno, Florida, known for its boating, fishing, and waterfront dining.

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_69f76eb386d88190a8d511aa11540dfc completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5b6bb60c81909f954227eebfb026 completed May 6, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4063a3c8ac81909d2d4b4bf544a643 completed June 27, 2026, 11:58 p.m.
NEDg Description generation batch_6a406777afd881908bbc1df6ff466b82 completed June 28, 2026, 12:14 a.m.
NED2 Entity disambiguation (via description) batch_6a4067e7fc2c81908c0567a29d6d1e3e completed June 28, 2026, 12:16 a.m.
Created at: May 3, 2026, 4:16 p.m.