Triple
T11979559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bolivian Primera División |
E285121
|
entity |
| Predicate | hasMemberClub |
P28388
|
FINISHED |
| Object |
Blooming
Blooming is a professional football club from Bolivia that competes in the country's top-tier league.
|
E958036
|
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: Blooming | Statement: [Bolivian Primera División, hasMemberClub, Blooming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blooming Context triple: [Bolivian Primera División, hasMemberClub, Blooming]
-
A.
The Bloom
"The Bloom" is the popular nickname for the Shenandoah Apple Blossom Festival, a long-running spring celebration in Winchester, Virginia featuring parades, concerts, and community events.
-
B.
Bloom
Bloom is a large open-access multilingual language model developed by the BigScience research workshop for text generation and understanding tasks.
-
C.
Bloom
Bloom is a common English and Jewish surname borne by numerous notable figures in literature, academia, and the arts.
-
D.
Blossom Time
Blossom Time is a popular operetta adapted from the music of Franz Schubert, known for its romantic story and melodic score.
-
E.
The Flower
The Flower is the nickname of Guy Lafleur, the legendary Montreal Canadiens right winger renowned for his speed, scoring prowess, and flowing blond hair.
- 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: Blooming Triple: [Bolivian Primera División, hasMemberClub, Blooming]
Generated description
Blooming is a professional football club from Bolivia that competes in the country's top-tier league.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Blooming Target entity description: Blooming is a professional football club from Bolivia that competes in the country's top-tier league.
-
A.
The Bloom
"The Bloom" is the popular nickname for the Shenandoah Apple Blossom Festival, a long-running spring celebration in Winchester, Virginia featuring parades, concerts, and community events.
-
B.
Bloom
Bloom is a large open-access multilingual language model developed by the BigScience research workshop for text generation and understanding tasks.
-
C.
Bloom
Bloom is a common English and Jewish surname borne by numerous notable figures in literature, academia, and the arts.
-
D.
Blossom Time
Blossom Time is a popular operetta adapted from the music of Franz Schubert, known for its romantic story and melodic score.
-
E.
The Flower
The Flower is the nickname of Guy Lafleur, the legendary Montreal Canadiens right winger renowned for his speed, scoring prowess, and flowing blond hair.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90393cfb08190b5b45d3e5e32fad3 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f47209bd088190bf4c7687c0a5eed6 |
completed | May 1, 2026, 9:27 a.m. |
| NEDg | Description generation | batch_69f47b7ac4048190ae09f18f1a90338f |
completed | May 1, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f47db91f38819092b7b5c5e2bb489b |
completed | May 1, 2026, 10:17 a.m. |
Created at: April 8, 2026, 9:46 p.m.