Triple

T17522519
Position Surface form Disambiguated ID Type / Status
Subject Ryde Bridge E426708 entity
Predicate hasApproachRoad P4067 FINISHED
Object Concord Road
Concord Road is a major arterial roadway in Sydney’s inner west that connects the suburb of Concord to key routes across the Parramatta River and beyond.
E1828575 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: Concord Road | Statement: [Ryde Bridge, hasApproachRoad, Concord Road]
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: Concord Road
Triple: [Ryde Bridge, hasApproachRoad, Concord Road]
Generated description
Concord Road is a major arterial roadway in Sydney’s inner west that connects the suburb of Concord to key routes across the Parramatta River and beyond.

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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d40ee08190b79d8e3d7f1b1272 completed April 19, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc34b59508190b1587ae59de04eef completed May 31, 2026, 11:24 p.m.
NEDg Description generation batch_6a1cc44ac1448190b0dc305eb5e460be completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc571b3b481908c523e5bad5e086a completed May 31, 2026, 11:34 p.m.
Created at: April 10, 2026, 5:49 a.m.