Triple

T26556731
Position Surface form Disambiguated ID Type / Status
Subject Daniel L. Doctoroff E666127 entity
Predicate notableProject P4 FINISHED
Object Sidewalk Toronto smart city proposal
The Sidewalk Toronto smart city proposal was an ambitious but ultimately cancelled plan to develop a high-tech, data-driven waterfront neighborhood in Toronto led by Alphabet’s Sidewalk Labs.
E1731926 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: Sidewalk Toronto smart city proposal | Statement: [Daniel L. Doctoroff, notableProject, Sidewalk Toronto smart city proposal]
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: Sidewalk Toronto smart city proposal
Triple: [Daniel L. Doctoroff, notableProject, Sidewalk Toronto smart city proposal]
Generated description
The Sidewalk Toronto smart city proposal was an ambitious but ultimately cancelled plan to develop a high-tech, data-driven waterfront neighborhood in Toronto led by Alphabet’s Sidewalk Labs.

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_69ee9cf7e94481909f0d556b36e43572 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f6146709fc81909851677f0cd4e2d7 completed May 2, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c82205a08190a5e5f7a91593b55e completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c945273c8190ac0bc6fe508a6d9a completed May 23, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca6f162c8190a8c7fbc1e188ea90 completed May 23, 2026, 3:40 p.m.
Created at: April 27, 2026, 1:50 a.m.