Triple

T10973889
Position Surface form Disambiguated ID Type / Status
Subject Tony Sanneh E259318 entity
Predicate familyName P18 FINISHED
Object Sanneh
Sanneh is a surname most notably associated with American soccer player Tony Sanneh.
 E896852 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: Sanneh | Statement: [Tony Sanneh, familyName, Sanneh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sanneh
Context triple: [Tony Sanneh, familyName, Sanneh]
  • A. Ngola
    Ngola is an alternative name for the Angolar people, a community of African descent primarily associated with São Tomé and Príncipe.
  • B. Djiba
    Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
  • C. Ngoni
    Ngoni is a Bantu language spoken by the Ngoni people of parts of Malawi, Tanzania, Mozambique, and Zambia, reflecting historical migrations from the Zulu region.
  • D. Mansa
    Mansa was the royal title used by the rulers of the Mali Empire, most famously borne by Mansa Musa, one of the wealthiest and most influential monarchs in history.
  • E. Mansa
    Mansa is a city in the Malwa region of Punjab, India, known primarily as an agricultural and cotton-growing center.
  • 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: Sanneh
Triple: [Tony Sanneh, familyName, Sanneh]
Generated description
Sanneh is a surname most notably associated with American soccer player Tony Sanneh.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sanneh
Target entity description: Sanneh is a surname most notably associated with American soccer player Tony Sanneh.
  • A. Ngola
    Ngola is an alternative name for the Angolar people, a community of African descent primarily associated with São Tomé and Príncipe.
  • B. Djiba
    Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
  • C. Ngoni
    Ngoni is a Bantu language spoken by the Ngoni people of parts of Malawi, Tanzania, Mozambique, and Zambia, reflecting historical migrations from the Zulu region.
  • D. Mansa
    Mansa was the royal title used by the rulers of the Mali Empire, most famously borne by Mansa Musa, one of the wealthiest and most influential monarchs in history.
  • E. Mansa
    Mansa is a city in the Malwa region of Punjab, India, known primarily as an agricultural and cotton-growing center.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d771f3794c8190b1992b4695139b62 completed April 9, 2026, 9:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7a0b3dc819084fbda3227caf5b5 completed April 18, 2026, 1 a.m.
NEDg Description generation batch_69e2ff211ae88190a40380cd25a61812 completed April 18, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69e32634397481908284c04448274b25 completed April 18, 2026, 6:35 a.m.
Created at: April 8, 2026, 9:24 p.m.