Triple

T30957600
Position Surface form Disambiguated ID Type / Status
Subject Quebec City E788719 entity
Predicate riverConfluence P11843 FINISHED
Object Saint Charles River
The Saint Charles River is a small river in Quebec City, Canada, that flows through the urban area and into the Saint Lawrence River, playing an important historical and recreational role in the city.
 E1963845 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 Charles River | Statement: [Quebec City, riverConfluence, Saint Charles River]
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 Charles River
Triple: [Quebec City, riverConfluence, Saint Charles River]
Generated description
The Saint Charles River is a small river in Quebec City, Canada, that flows through the urban area and into the Saint Lawrence River, playing an important historical and recreational role in the city.

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_69f224c28c1881908c33b45d689f1724 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6934ac07c8190b85541dc38e19a23 completed May 3, 2026, 12:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b074fb46c8190a21ca08527870c81 completed June 11, 2026, 7:06 p.m.
NEDg Description generation batch_6a2b0bf7b9788190af18130254a846b4 completed June 11, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a2b0c519db0819093c1913497020eab completed June 11, 2026, 7:28 p.m.
Created at: April 29, 2026, 8:54 p.m.