Triple
T15643094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bacău |
E376112
|
entity |
| Predicate | hasSportsTeam |
P330
|
FINISHED |
| Object |
CSM Bacău
CSM Bacău is a Romanian multi-sport club based in the city of Bacău, known for competing in various national sports competitions.
|
E1170386
|
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: CSM Bacău | Statement: [Bacău, hasSportsTeam, CSM Bacău]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CSM Bacău Context triple: [Bacău, hasSportsTeam, CSM Bacău]
-
A.
FCM Bacău
FCM Bacău is a Romanian football club based in the city of Bacău.
-
B.
FC Bihor Oradea
FC Bihor Oradea is a Romanian professional football club based in Oradea, known for competing in the national league system and developing notable Romanian players.
-
C.
FC Baia Mare
FC Baia Mare is a Romanian football club known for its regional prominence and history of developing local talent.
-
D.
CFR Cluj
CFR Cluj is a prominent Romanian professional football club known for its multiple national league titles and regular appearances in European competitions.
-
E.
FC Vaslui
FC Vaslui was a Romanian professional football club from the city of Vaslui that competed in Liga I and became known for its rapid rise and strong performances in the late 2000s and early 2010s.
- 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: CSM Bacău Triple: [Bacău, hasSportsTeam, CSM Bacău]
Generated description
CSM Bacău is a Romanian multi-sport club based in the city of Bacău, known for competing in various national sports competitions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CSM Bacău Target entity description: CSM Bacău is a Romanian multi-sport club based in the city of Bacău, known for competing in various national sports competitions.
-
A.
FCM Bacău
FCM Bacău is a Romanian football club based in the city of Bacău.
-
B.
FC Bihor Oradea
FC Bihor Oradea is a Romanian professional football club based in Oradea, known for competing in the national league system and developing notable Romanian players.
-
C.
FC Baia Mare
FC Baia Mare is a Romanian football club known for its regional prominence and history of developing local talent.
-
D.
CFR Cluj
CFR Cluj is a prominent Romanian professional football club known for its multiple national league titles and regular appearances in European competitions.
-
E.
FC Vaslui
FC Vaslui was a Romanian professional football club from the city of Vaslui that competed in Liga I and became known for its rapid rise and strong performances in the late 2000s and early 2010s.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed23d688190bea996f90989d406 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6790f2288190add8ab0bc0f114bf |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff6bc27ef481908f5125ab553b5015 |
completed | May 9, 2026, 5:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6c214c7881908ac483dbb8d08f29 |
completed | May 9, 2026, 5:17 p.m. |
Created at: April 10, 2026, 4:15 a.m.