Triple

T27124000
Position Surface form Disambiguated ID Type / Status
Subject University City, Charlotte E687072 entity
Predicate hasShoppingCenter P1495 FINISHED
Object The Shoppes at University Place
The Shoppes at University Place is an open-air retail and dining complex built around a scenic lake in Charlotte’s University City area.
E1757571 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: The Shoppes at University Place | Statement: [University City, Charlotte, hasShoppingCenter, The Shoppes at University Place]
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: The Shoppes at University Place
Triple: [University City, Charlotte, hasShoppingCenter, The Shoppes at University Place]
Generated description
The Shoppes at University Place is an open-air retail and dining complex built around a scenic lake in Charlotte’s University City area.

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_69ef148c2b588190afc15b529f7af845 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6244611048190aa6c58e99418827f completed May 2, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12481925308190a0a239bf011ed315 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a1248bb58a48190ae84e7b538b10503 completed May 24, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_6a124973e3c88190898b0cece69419b3 completed May 24, 2026, 12:42 a.m.
Created at: April 27, 2026, 9 a.m.