Triple

T30851483
Position Surface form Disambiguated ID Type / Status
Subject Roseland community area E785791 entity
Predicate hasMajorStreet P30026 FINISHED
Object 103rd Street
103rd Street is a major east–west thoroughfare on the South Side of Chicago that runs through the Roseland community area.
 E1971031 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: 103rd Street | Statement: [Roseland community area, hasMajorStreet, 103rd Street]
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: 103rd Street
Triple: [Roseland community area, hasMajorStreet, 103rd Street]
Generated description
103rd Street is a major east–west thoroughfare on the South Side of Chicago that runs through the Roseland community area.

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_69f224b850848190a4af4ccf8ddadcdf completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6917c8d8c8190b4091f3ef57834bb completed May 3, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79ad4f248190844af3d093c3623e completed June 12, 2026, 3:14 a.m.
NEDg Description generation batch_6a2b7ae829ac8190816c4c7ffdfc3a1c completed June 12, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7bdca59c81909eeabf535985fd97 completed June 12, 2026, 3:24 a.m.
Created at: April 29, 2026, 8:46 p.m.