Triple
T16231173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eskişehirspor |
E393982
|
entity |
| Predicate | foundedByMergerOf |
P6637
|
FINISHED |
| Object |
Akınspor
Akınspor was a Turkish football club that became one of the predecessor teams merged to form Eskişehirspor.
|
E1200599
|
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: Akınspor | Statement: [Eskişehirspor, foundedByMergerOf, Akınspor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akınspor Context triple: [Eskişehirspor, foundedByMergerOf, Akınspor]
-
A.
Adanaspor
Adanaspor is a professional Turkish football club based in Adana that competes in the country’s league system and has featured various international players.
-
B.
Konyaspor
Konyaspor is a professional Turkish football club based in Konya that competes in the country’s top leagues and has a passionate regional fan base.
-
C.
Kayserispor
Kayserispor is a professional Turkish football club based in Kayseri that competes in the country’s top leagues.
-
D.
Boluspor
Boluspor is a Turkish professional football club based in the city of Bolu that competes in the country’s football league system.
-
E.
Sakaryaspor
Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
- 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: Akınspor Triple: [Eskişehirspor, foundedByMergerOf, Akınspor]
Generated description
Akınspor was a Turkish football club that became one of the predecessor teams merged to form Eskişehirspor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Akınspor Target entity description: Akınspor was a Turkish football club that became one of the predecessor teams merged to form Eskişehirspor.
-
A.
Adanaspor
Adanaspor is a professional Turkish football club based in Adana that competes in the country’s league system and has featured various international players.
-
B.
Konyaspor
Konyaspor is a professional Turkish football club based in Konya that competes in the country’s top leagues and has a passionate regional fan base.
-
C.
Kayserispor
Kayserispor is a professional Turkish football club based in Kayseri that competes in the country’s top leagues.
-
D.
Boluspor
Boluspor is a Turkish professional football club based in the city of Bolu that competes in the country’s football league system.
-
E.
Sakaryaspor
Sakaryaspor is a Turkish professional football club known for developing notable talents such as legendary striker Hakan Şükür.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d29fa248190943f4c3f7808908b |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007a0ab08819082aea4c312c9ffc7 |
completed | May 10, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_6a00098ea3e48190b0744f1eafab9ce2 |
completed | May 10, 2026, 4:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0009fb40a48190b82f6de80226d306 |
completed | May 10, 2026, 4:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.