Triple

T16473211
Position Surface form Disambiguated ID Type / Status
Subject Piscop E400118 entity
Predicate locatedNear P294 FINISHED
Object Paris
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
 E568 NE FINISHED

How this triple was built (4 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: Paris | Statement: [Piscop, locatedNear, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris
Context triple: [Piscop, locatedNear, Paris]
  • A. Paris
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • C. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • D. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • E. Paris
    Paris was an enslaved man held in bondage by George Washington at the President's House in Philadelphia during his presidency.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Paris
Triple: [Piscop, locatedNear, Paris]
Generated description
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris
Target entity description: Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • A. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • C. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • D. Paris
    "Paris" is a hit electronic-pop single by The Chainsmokers, known for its nostalgic lyrics and mellow, atmospheric production.
  • E. Paris
    "Paris" is a 2017 electronic dance music single by The Chainsmokers that became a major international hit.
  • F. None of above.

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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32dd266c48190991a1484eb2f7bcc completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f457b8c8190b278697ef43301cb completed May 10, 2026, 9:26 a.m.
NEDg Description generation batch_6a004ff9e2e88190afa4726e3ba71ea9 completed May 10, 2026, 9:29 a.m.
NED2 Entity disambiguation (via description) batch_6a00505beaa881909aca531af1149fbc completed May 10, 2026, 9:31 a.m.
Created at: April 10, 2026, 5:11 a.m.