Triple
T5248830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syrianska FC |
E118529
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Syrianska
Syrianska is a Swedish football club traditionally associated with the Assyrian/Syriac community, based in Södertälje.
|
E505490
|
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: Syrianska | Statement: [Syrianska FC, shortName, Syrianska]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Syrianska Context triple: [Syrianska FC, shortName, Syrianska]
-
A.
Syrian
Syrian refers to a person from Syria or of Syrian heritage, associated with the country’s Arab-majority culture and diverse historical and ethnic background.
-
B.
Turoyo
Turoyo is a modern Neo-Aramaic language traditionally spoken by Syriac Orthodox Christian communities from the Tur Abdin region of southeastern Turkey and neighboring areas.
-
C.
Turiysk
Turiysk is a small town in western Ukraine known for its historical roots and location within the Volyn region.
-
D.
Syriac
Syriac is a dialect of Middle Aramaic that became a major literary and liturgical language of early Eastern Christianity and the Syriac Church tradition.
-
E.
Seraiki
Seraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
- 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: Syrianska Triple: [Syrianska FC, shortName, Syrianska]
Generated description
Syrianska is a Swedish football club traditionally associated with the Assyrian/Syriac community, based in Södertälje.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Syrianska Target entity description: Syrianska is a Swedish football club traditionally associated with the Assyrian/Syriac community, based in Södertälje.
-
A.
Syrian
Syrian refers to a person from Syria or of Syrian heritage, associated with the country’s Arab-majority culture and diverse historical and ethnic background.
-
B.
Turoyo
Turoyo is a modern Neo-Aramaic language traditionally spoken by Syriac Orthodox Christian communities from the Tur Abdin region of southeastern Turkey and neighboring areas.
-
C.
Turiysk
Turiysk is a small town in western Ukraine known for its historical roots and location within the Volyn region.
-
D.
Syriac
Syriac is a dialect of Middle Aramaic that became a major literary and liturgical language of early Eastern Christianity and the Syriac Church tradition.
-
E.
Seraiki
Seraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b787b34819081af96de9355bb4f |
completed | March 20, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef83998f881909fef2746f5c496af |
completed | March 21, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69befa746be88190a8d807317ab36430 |
completed | March 21, 2026, 8:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69befac54e8c8190986aca0f5591d04e |
completed | March 21, 2026, 8:08 p.m. |
Created at: March 20, 2026, 1:50 p.m.