Triple
T22680203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleppo Eyalet |
E560458
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object |
Marash
Marash is a historic city in southern Anatolia, known today as Kahramanmaraş in modern Turkey.
|
E1549193
|
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: Marash | Statement: [Aleppo Eyalet, majorCity, Marash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marash Context triple: [Aleppo Eyalet, majorCity, Marash]
-
A.
Mardin
Mardin is a historic city in southeastern Turkey known for its terraced stone architecture, diverse ethnic and religious heritage, and commanding views over the Mesopotamian plains.
-
B.
Havsa
Havsa is a town in northwestern Turkey’s Edirne Province, historically notable as the place where Ottoman Sultan Bayezid II died.
-
C.
Adana
Adana is a major city in southern Turkey known as an important agricultural, industrial, and transportation hub of the Çukurova region.
-
D.
Gedera
Gedera is a town in central Israel known for its agricultural roots and diverse immigrant communities.
-
E.
Serdivan
Serdivan is a rapidly developing district and suburban area of the city of Sakarya in northwestern Turkey, known for its residential neighborhoods, university presence, and growing commercial centers.
- 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: Marash Triple: [Aleppo Eyalet, majorCity, Marash]
Generated description
Marash is a historic city in southern Anatolia, known today as Kahramanmaraş in modern Turkey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marash Target entity description: Marash is a historic city in southern Anatolia, known today as Kahramanmaraş in modern Turkey.
-
A.
Mardin
Mardin is a historic city in southeastern Turkey known for its terraced stone architecture, diverse ethnic and religious heritage, and commanding views over the Mesopotamian plains.
-
B.
Havsa
Havsa is a town in northwestern Turkey’s Edirne Province, historically notable as the place where Ottoman Sultan Bayezid II died.
-
C.
Adana
Adana is a major city in southern Turkey known as an important agricultural, industrial, and transportation hub of the Çukurova region.
-
D.
Gedera
Gedera is a town in central Israel known for its agricultural roots and diverse immigrant communities.
-
E.
Serdivan
Serdivan is a rapidly developing district and suburban area of the city of Sakarya in northwestern Turkey, known for its residential neighborhoods, university presence, and growing commercial centers.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785f68b4819082c5570f741f5135 |
completed | April 29, 2026, 3:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b73f2e9ec8190b8dd114b99990faa |
completed | May 18, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_6a0b75dd6214819088a62ec842f0493b |
completed | May 18, 2026, 8:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b76ab5cdc8190be190e8980869ba0 |
completed | May 18, 2026, 8:29 p.m. |
Created at: April 17, 2026, 3:11 p.m.