Triple

T22289512
Position Surface form Disambiguated ID Type / Status
Subject 1990 FIFA World Cup All-Star Team E550954 entity
Predicate includesPlayer P29723 FINISHED
Object Giuseppe Giannini
Giuseppe Giannini is a former Italian attacking midfielder best known as a Roma icon and key playmaker for Italy’s national team in the late 1980s and early 1990s.
E1779839 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: Giuseppe Giannini | Statement: [1990 FIFA World Cup All-Star Team, includesPlayer, Giuseppe Giannini]
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: Giuseppe Giannini
Triple: [1990 FIFA World Cup All-Star Team, includesPlayer, Giuseppe Giannini]
Generated description
Giuseppe Giannini is a former Italian attacking midfielder best known as a Roma icon and key playmaker for Italy’s national team in the late 1980s and early 1990s.

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_69e11e45fb848190a1b2ae21296e3a5f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1560adde88190961d8fc24c1c4b3c completed April 29, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0a179d081909d8e3369afb277f0 completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d169e8888190bf3c8e7f0718a3a5 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d26af1288190a2925d726ab5be31 completed May 24, 2026, 10:26 a.m.
Created at: April 16, 2026, 8:41 p.m.