Triple

T27312152
Position Surface form Disambiguated ID Type / Status
Subject South Minneapolis E689237 entity
Predicate containsNeighborhood P4813 FINISHED
Object Hale
Hale is a primarily residential neighborhood in south Minneapolis known for its quiet streets, parks, and proximity to Lake Nokomis.
E1766425 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: Hale | Statement: [South Minneapolis, containsNeighborhood, Hale]
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: Hale
Triple: [South Minneapolis, containsNeighborhood, Hale]
Generated description
Hale is a primarily residential neighborhood in south Minneapolis known for its quiet streets, parks, and proximity to Lake Nokomis.

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_69ef355c53a08190a8a92e355a7ce115 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627b403d0819083ef8ed23f802e35 completed May 2, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a129cb2fb788190aaaecddaacc72280 completed May 24, 2026, 6:37 a.m.
NEDg Description generation batch_6a129e256d0c8190874e54b63227ce0a completed May 24, 2026, 6:43 a.m.
NED2 Entity disambiguation (via description) batch_6a129ebbbf288190afbb4f21249a6fcf completed May 24, 2026, 6:46 a.m.
Created at: April 27, 2026, 11:28 a.m.