Triple

T31836132
Position Surface form Disambiguated ID Type / Status
Subject Palais Montcalm E812677 entity
Predicate near P350 FINISHED
Object Saint-Jean Street, Quebec City
Saint-Jean Street in Quebec City is a historic and bustling thoroughfare known for its shops, restaurants, and cultural attractions within the city’s old urban core.
E1980031 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: Saint-Jean Street, Quebec City | Statement: [Palais Montcalm, near, Saint-Jean Street, Quebec City]
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: Saint-Jean Street, Quebec City
Triple: [Palais Montcalm, near, Saint-Jean Street, Quebec City]
Generated description
Saint-Jean Street in Quebec City is a historic and bustling thoroughfare known for its shops, restaurants, and cultural attractions within the city’s old 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_69f348ea7ffc8190a2ab43d80277cf59 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aff1cb888190832f3c7785dedd1d completed May 3, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e65a92a7c81909172cc39207325a2 completed June 14, 2026, 8:26 a.m.
NEDg Description generation batch_6a2e6811e32481908dedf8ac86f51cae completed June 14, 2026, 8:36 a.m.
NED2 Entity disambiguation (via description) batch_6a2e68c8ce34819092378c1460fe4ef8 completed June 14, 2026, 8:39 a.m.
Created at: April 30, 2026, 11:48 p.m.