Triple

T3015410
Position Surface form Disambiguated ID Type / Status
Subject Marco Polo E82324 entity
Predicate familyName P18 FINISHED
Object Polo
Polo is the surname of the Venetian merchant and explorer Marco Polo, famed for his extensive travels through Asia and detailed accounts of the Mongol Empire.
 E317843 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: Polo | Statement: [Marco Polo, familyName, Polo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Polo
Context triple: [Marco Polo, familyName, Polo]
  • A. Polo Fields
    Polo Fields is a large multi-use athletic and event venue in San Francisco’s Golden Gate Park, historically used for polo and now popular for running, cycling, concerts, and recreational sports.
  • B. Carreras
    Carreras is a Spanish surname most famously associated with José Carreras, the renowned operatic tenor and member of The Three Tenors.
  • C. Speedway
    Speedway is a small town in Marion County, Indiana, best known as the home of the Indianapolis Motor Speedway and the Indianapolis 500 auto race.
  • D. Bola
    Bola is the given name of Bola Tinubu, a prominent Nigerian politician and current president of Nigeria.
  • E. El Golf
    El Golf is a Santiago Metro station on Line 1 located in the upscale financial and commercial district of Las Condes, Santiago, Chile.
  • 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: Polo
Triple: [Marco Polo, familyName, Polo]
Generated description
Polo is the surname of the Venetian merchant and explorer Marco Polo, famed for his extensive travels through Asia and detailed accounts of the Mongol Empire.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Polo
Target entity description: Polo is the surname of the Venetian merchant and explorer Marco Polo, famed for his extensive travels through Asia and detailed accounts of the Mongol Empire.
  • A. Polo Fields
    Polo Fields is a large multi-use athletic and event venue in San Francisco’s Golden Gate Park, historically used for polo and now popular for running, cycling, concerts, and recreational sports.
  • B. Carreras
    Carreras is a Spanish surname most famously associated with José Carreras, the renowned operatic tenor and member of The Three Tenors.
  • C. Speedway
    Speedway is a small town in Marion County, Indiana, best known as the home of the Indianapolis Motor Speedway and the Indianapolis 500 auto race.
  • D. Bola
    Bola is the given name of Bola Tinubu, a prominent Nigerian politician and current president of Nigeria.
  • E. El Golf
    El Golf is a Santiago Metro station on Line 1 located in the upscale financial and commercial district of Las Condes, Santiago, Chile.
  • F. None of above. chosen

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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a6b37288190a6965d183ca4b08b completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6b78448190beb41460314278ec completed March 11, 2026, 8:57 a.m.
NEDg Description generation batch_69b12faf75ac81909031430d58919c95 completed March 11, 2026, 9:02 a.m.
NED2 Entity disambiguation (via description) batch_69b1c7d3f2c88190aa26d8d12777b2a2 completed March 11, 2026, 7:51 p.m.
Created at: March 8, 2026, 3 p.m.