Triple

T29487185
Position Surface form Disambiguated ID Type / Status
Subject Florida State Road 997 E747959 entity
Predicate formerName P65 FINISHED
Object State Road 27
State Road 27 is a former designation for a Florida state highway now known as State Road 997, which runs through Miami-Dade County as a major north–south route west of the urban core.
E1934116 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: State Road 27 | Statement: [Florida State Road 997, formerName, State Road 27]
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: State Road 27
Triple: [Florida State Road 997, formerName, State Road 27]
Generated description
State Road 27 is a former designation for a Florida state highway now known as State Road 997, which runs through Miami-Dade County as a major north–south route west of the urban core.

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_69f0bd43ba30819095eb1cfc3adf525c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c06bbc48190b97efd782ebc81e6 completed May 2, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbb813408190bbcce8e20574169e completed June 10, 2026, 1:19 a.m.
NEDg Description generation batch_6a28be620bac8190b2a5b8298d2e3303 completed June 10, 2026, 1:31 a.m.
NED2 Entity disambiguation (via description) batch_6a28bf4385848190a8059a2fdc7134d0 completed June 10, 2026, 1:34 a.m.
Created at: April 28, 2026, 4:09 p.m.