Triple
T19281976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drew Barry |
E482210
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object |
Metis Varese
Metis Varese is an Italian professional basketball club based in Varese, historically known as one of Europe’s most successful teams.
|
E1367285
|
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: Metis Varese | Statement: [Drew Barry, memberOfSportsTeam, Metis Varese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metis Varese Context triple: [Drew Barry, memberOfSportsTeam, Metis Varese]
-
A.
Fancelli
Fancelli is an Italian surname associated with figures such as Renaissance sculptor Domenico Fancelli.
-
B.
Orio Litta
Orio Litta is a small municipality in the Lombardy region of northern Italy, known for its location along the historic Via Francigena pilgrimage route.
-
C.
Viterelli
Viterelli is an Italian surname most notably associated with Joe Viterelli, an American character actor known for his mobster roles in films like "Analyze This."
-
D.
Tamburini
Tamburini is an Italian-origin surname borne by various notable figures, including architects, musicians, and designers.
-
E.
Piermarini
Piermarini is an Italian surname most notably associated with Giuseppe Piermarini, an 18th-century architect renowned for designing Milan’s Teatro alla Scala.
- 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: Metis Varese Triple: [Drew Barry, memberOfSportsTeam, Metis Varese]
Generated description
Metis Varese is an Italian professional basketball club based in Varese, historically known as one of Europe’s most successful teams.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Metis Varese Target entity description: Metis Varese is an Italian professional basketball club based in Varese, historically known as one of Europe’s most successful teams.
-
A.
Fancelli
Fancelli is an Italian surname associated with figures such as Renaissance sculptor Domenico Fancelli.
-
B.
Orio Litta
Orio Litta is a small municipality in the Lombardy region of northern Italy, known for its location along the historic Via Francigena pilgrimage route.
-
C.
Viterelli
Viterelli is an Italian surname most notably associated with Joe Viterelli, an American character actor known for his mobster roles in films like "Analyze This."
-
D.
Tamburini
Tamburini is an Italian-origin surname borne by various notable figures, including architects, musicians, and designers.
-
E.
Piermarini
Piermarini is an Italian surname most notably associated with Giuseppe Piermarini, an 18th-century architect renowned for designing Milan’s Teatro alla Scala.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbff1e6c819094ae6a5ad40adb65 |
completed | April 20, 2026, 10:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a070e7ba04481908e8b707d34028e58 |
completed | May 15, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_6a070f74709481909b4eb1c073db2134 |
completed | May 15, 2026, 12:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a070fccff7c819083fe388dda8e4e5a |
completed | May 15, 2026, 12:21 p.m. |
Created at: April 10, 2026, 1:30 p.m.