Triple

T38067856
Position Surface form Disambiguated ID Type / Status
Subject street network of Tallahassee E950518 entity
Predicate includesRoad P85887 FINISHED
Object Adams Street
Adams Street is a notable roadway in Tallahassee, Florida, running through the city's downtown area and connecting key civic and commercial locations.
 E2293437 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: Adams Street | Statement: [street network of Tallahassee, includesRoad, Adams 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: Adams Street
Triple: [street network of Tallahassee, includesRoad, Adams Street]
Generated description
Adams Street is a notable roadway in Tallahassee, Florida, running through the city's downtown area and connecting key civic and commercial locations.

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_69f76f02a6c48190a94f3c0b3ee90cf2 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbca3ba8a48190a234a688be7b1f6a completed May 6, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7aa8cbab088190b62d060779606fcf completed Aug. 11, 2026, 4:44 a.m.
NEDg Description generation batch_6a7aa97357408190a09d63683851f5da completed Aug. 11, 2026, 4:47 a.m.
NED2 Entity disambiguation (via description) batch_6a7aa9fbae7881908349dd1f226e05d7 completed Aug. 11, 2026, 4:50 a.m.
Created at: May 3, 2026, 4:21 p.m.