Triple

T9917619
Position Surface form Disambiguated ID Type / Status
Subject Eastern Point E185909 entity
Predicate locatedIn P40 FINISHED
Object Gloucester, Massachusetts
Gloucester, Massachusetts is a historic coastal city on Cape Ann known for its long-standing fishing industry, maritime heritage, and scenic New England seascapes.
E2284578 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: Gloucester, Massachusetts | Statement: [Eastern Point, locatedIn, Gloucester, Massachusetts]
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: Gloucester, Massachusetts
Triple: [Eastern Point, locatedIn, Gloucester, Massachusetts]
Generated description
Gloucester, Massachusetts is a historic coastal city on Cape Ann known for its long-standing fishing industry, maritime heritage, and scenic New England seascapes.

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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb5673f108190914e0c172dddc65f completed April 2, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a43c15befd08190ad78afbea1b3f0cb completed June 30, 2026, 1:15 p.m.
NEDg Description generation batch_6a43c1b6c21481908da5ac9685d1add4 completed June 30, 2026, 1:16 p.m.
NED2 Entity disambiguation (via description) batch_6a43c279b8c881908882b8868ff78638 completed June 30, 2026, 1:19 p.m.
Created at: March 30, 2026, 8:42 p.m.