Triple
T12525478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FC Aktobe |
E299426
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object |
Aktyubinets
Aktyubinets is the former name of FC Aktobe, a professional football club based in Aktobe, Kazakhstan.
|
E988238
|
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: Aktyubinets | Statement: [FC Aktobe, formerName, Aktyubinets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aktyubinets Context triple: [FC Aktobe, formerName, Aktyubinets]
-
A.
Tupolski
Tupolski is a hard-edged, morally ambiguous police detective in Martin McDonagh’s dark play "The Pillowman," known for his interrogations and psychological manipulation.
-
B.
Sapsan
Sapsan is a high-speed passenger train service in Russia operated by Russian Railways, primarily running between Moscow and St. Petersburg.
-
C.
Shapuri
Shapuri is a regional dialect of the Lahnda (Western Punjabi) language spoken in parts of Pakistan’s Punjab region.
-
D.
Sovbez
Sovbez is the powerful advisory body in Russia that coordinates national security and defense policy under the leadership of the president.
-
E.
Beilein
Beilein is a surname most prominently associated with American basketball coach John Beilein, known for his successful collegiate coaching career.
- 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: Aktyubinets Triple: [FC Aktobe, formerName, Aktyubinets]
Generated description
Aktyubinets is the former name of FC Aktobe, a professional football club based in Aktobe, Kazakhstan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aktyubinets Target entity description: Aktyubinets is the former name of FC Aktobe, a professional football club based in Aktobe, Kazakhstan.
-
A.
Tupolski
Tupolski is a hard-edged, morally ambiguous police detective in Martin McDonagh’s dark play "The Pillowman," known for his interrogations and psychological manipulation.
-
B.
Sapsan
Sapsan is a high-speed passenger train service in Russia operated by Russian Railways, primarily running between Moscow and St. Petersburg.
-
C.
Shapuri
Shapuri is a regional dialect of the Lahnda (Western Punjabi) language spoken in parts of Pakistan’s Punjab region.
-
D.
Sovbez
Sovbez is the powerful advisory body in Russia that coordinates national security and defense policy under the leadership of the president.
-
E.
Beilein
Beilein is a surname most prominently associated with American basketball coach John Beilein, known for his successful collegiate coaching career.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9545d7e6c819080c3a85c18caa1ae |
completed | April 10, 2026, 7:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bc393808190add527030a928517 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64c535c9881908e5bf07d13fa73c5 |
completed | May 2, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6508afef08190ac7a19b1ee90141e |
completed | May 2, 2026, 7:29 p.m. |
Created at: April 8, 2026, 9:57 p.m.