Triple

T31423067
Position Surface form Disambiguated ID Type / Status
Subject Anastasia Island E801582 entity
Predicate accessedBy P1985 FINISHED
Object State Road 312
State Road 312 is a Florida state highway in St. Johns County that serves as an east–west connector between the mainland city of St. Augustine and Anastasia Island.
E1964069 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 312 | Statement: [Anastasia Island, accessedBy, State Road 312]
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 312
Triple: [Anastasia Island, accessedBy, State Road 312]
Generated description
State Road 312 is a Florida state highway in St. Johns County that serves as an east–west connector between the mainland city of St. Augustine and Anastasia Island.

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_69f348c26f048190b4adadd71b4596c5 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a0beb2cc8190bda62c76d1fce5cc completed May 3, 2026, 1:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b14487c088190adbb2fdad68d036e completed June 11, 2026, 8:02 p.m.
NEDg Description generation batch_6a2b14fb9b308190ad263463c0d2a5f4 completed June 11, 2026, 8:05 p.m.
NED2 Entity disambiguation (via description) batch_6a2b15aa5b1c8190bc2e6437bad1cc5e completed June 11, 2026, 8:08 p.m.
Created at: April 30, 2026, 8:50 p.m.