Triple
T7807462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayezid II |
E180590
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Dimetoka
Dimetoka is a historic town in present-day northeastern Greece, known for its medieval and Ottoman heritage.
|
E694478
|
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: Dimetoka | Statement: [Bayezid II, placeOfBirth, Dimetoka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dimetoka Context triple: [Bayezid II, placeOfBirth, Dimetoka]
-
A.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
B.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
-
C.
Bagamoyo
Bagamoyo is a historic coastal town in present-day Tanzania that served as a major 19th-century East African trade and colonial center, including as an early administrative hub for German rule.
-
D.
Mazabuka
Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
-
E.
Ngamo
Ngamo is a West Chadic language spoken primarily in northeastern Nigeria by the Ngamo people.
- 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: Dimetoka Triple: [Bayezid II, placeOfBirth, Dimetoka]
Generated description
Dimetoka is a historic town in present-day northeastern Greece, known for its medieval and Ottoman heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dimetoka Target entity description: Dimetoka is a historic town in present-day northeastern Greece, known for its medieval and Ottoman heritage.
-
A.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
B.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
-
C.
Bagamoyo
Bagamoyo is a historic coastal town in present-day Tanzania that served as a major 19th-century East African trade and colonial center, including as an early administrative hub for German rule.
-
D.
Mazabuka
Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
-
E.
Ngamo
Ngamo is a West Chadic language spoken primarily in northeastern Nigeria by the Ngamo people.
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf63b3ebc819088dcf4c58b80b18a |
completed | March 30, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb1450a2408190afe0459086d4480f |
completed | March 31, 2026, 12:24 a.m. |
| NEDg | Description generation | batch_69cb173190a88190b31fd7973bc19d43 |
completed | March 31, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a49beb4819090532acabb9391b1 |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:36 p.m.