Triple

T27792885
Position Surface form Disambiguated ID Type / Status
Subject Inter Allies FC E701129 entity
Predicate notableFormerPlayer P304 FINISHED
Object Isaac Twum
Isaac Twum is a Ghanaian professional footballer and midfielder known for captaining Ghana’s U-17 and U-23 national teams and playing in various African and European leagues.
E1793446 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: Isaac Twum | Statement: [Inter Allies FC, notableFormerPlayer, Isaac Twum]
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: Isaac Twum
Triple: [Inter Allies FC, notableFormerPlayer, Isaac Twum]
Generated description
Isaac Twum is a Ghanaian professional footballer and midfielder known for captaining Ghana’s U-17 and U-23 national teams and playing in various African and European leagues.

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_69ef6a50d8088190acbf3dfbb06d8091 completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f6380913a88190a338cf12f8b15c28 completed May 2, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13033f04808190bbda87ee806a337f completed May 24, 2026, 1:55 p.m.
NEDg Description generation batch_6a13044829448190905f994a78ac7871 completed May 24, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_6a130515074c81909e402d00ce95b85f completed May 24, 2026, 2:03 p.m.
Created at: April 27, 2026, 5:29 p.m.