Triple

T26247914
Position Surface form Disambiguated ID Type / Status
Subject Southampton Village Historic District E656499 entity
Predicate nearbyBodyOfWater P1489 FINISHED
Object Lake Agawam
Lake Agawam is a coastal freshwater lake in Southampton, New York, known for its scenic setting amid historic estates and its environmental challenges related to pollution and algal blooms.
E2296675 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: Lake Agawam | Statement: [Southampton Village Historic District, nearbyBodyOfWater, Lake Agawam]
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: Lake Agawam
Triple: [Southampton Village Historic District, nearbyBodyOfWater, Lake Agawam]
Generated description
Lake Agawam is a coastal freshwater lake in Southampton, New York, known for its scenic setting amid historic estates and its environmental challenges related to pollution and algal blooms.

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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60dc7d2a081908645d06c02dc3e02 completed May 2, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82a15090a081909ad8c2ec7506e805 completed Aug. 17, 2026, 5:51 a.m.
NEDg Description generation batch_6a82a1bdea8c81908ceaf7863f6f1453 completed Aug. 17, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_6a82a1f509ac819094522a55f5be021c completed Aug. 17, 2026, 5:53 a.m.
Created at: April 26, 2026, 9:06 p.m.