Triple
T15389734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandon Jennings |
E368007
|
entity |
| Predicate | playedFor |
P2170
|
FINISHED |
| Object |
Lottomatica Roma
Lottomatica Roma was a professional basketball club based in Rome, Italy, that competed in the country’s top league and European competitions.
|
E1154834
|
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: Lottomatica Roma | Statement: [Brandon Jennings, playedFor, Lottomatica Roma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lottomatica Roma Context triple: [Brandon Jennings, playedFor, Lottomatica Roma]
-
A.
Loto
Loto is a small village on Pukapuka Atoll in the Cook Islands, known for its traditional Polynesian community and remote Pacific island setting.
-
B.
Lotto Park
Lotto Park is a football stadium in Anderlecht, Brussels, best known as the historic home ground of Belgian club R.S.C. Anderlecht.
-
C.
Totesport
Totesport is a British betting and gaming company known for its involvement in horse racing and sports wagering.
-
D.
Lotto Arena
Lotto Arena is a multi-purpose indoor arena in the Merksem district of Antwerp, Belgium, hosting concerts, sports events, and other large-scale entertainment.
-
E.
TOTO
TOTO is the commonly used abbreviation for the Tongue of the Ocean, a deep, U-shaped submarine trench in the Bahamas.
- 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: Lottomatica Roma Triple: [Brandon Jennings, playedFor, Lottomatica Roma]
Generated description
Lottomatica Roma was a professional basketball club based in Rome, Italy, that competed in the country’s top league and European competitions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lottomatica Roma Target entity description: Lottomatica Roma was a professional basketball club based in Rome, Italy, that competed in the country’s top league and European competitions.
-
A.
Loto
Loto is a small village on Pukapuka Atoll in the Cook Islands, known for its traditional Polynesian community and remote Pacific island setting.
-
B.
Lotto Park
Lotto Park is a football stadium in Anderlecht, Brussels, best known as the historic home ground of Belgian club R.S.C. Anderlecht.
-
C.
Totesport
Totesport is a British betting and gaming company known for its involvement in horse racing and sports wagering.
-
D.
Lotto Arena
Lotto Arena is a multi-purpose indoor arena in the Merksem district of Antwerp, Belgium, hosting concerts, sports events, and other large-scale entertainment.
-
E.
TOTO
TOTO is the commonly used abbreviation for the Tongue of the Ocean, a deep, U-shaped submarine trench in the Bahamas.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e7727a081908eff45bbc1633c8a |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff134e37d881909f373b90a99fc067 |
completed | May 9, 2026, 10:58 a.m. |
| NEDg | Description generation | batch_69ff141b025c8190ac5ac9400ff36133 |
completed | May 9, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff1519100c819083ee0342bf25d89e |
completed | May 9, 2026, 11:06 a.m. |
Created at: April 10, 2026, 3:19 a.m.