Triple
T823103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaziantep |
E17791
|
entity |
| Predicate | receivedTitle |
P12204
|
FINISHED |
| Object |
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
|
E98410
|
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: Gazi | Statement: [Gaziantep, receivedTitle, Gazi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gazi Context triple: [Gaziantep, receivedTitle, Gazi]
-
A.
Mustafa
Mustafa is the given birth name of Mustafa Kemal Atatürk, the founder and first president of the Republic of Turkey.
-
B.
Giray
The Giray were the hereditary ruling dynasty of the Crimean Khanate, a prominent Turkic-Mongol royal house that claimed descent from Genghis Khan.
-
C.
Eskandar
Eskandar is a Persian and Arabic form of the name Alexander, commonly used in historical and literary contexts to refer to Alexander the Great.
-
D.
Atakule
Atakule is a prominent observation and communications tower in Ankara, Turkey, known for its panoramic city views and revolving restaurant.
-
E.
Orhan
Orhan was the second ruler of the early Ottoman state who significantly expanded its territories in northwestern Anatolia and laid foundations for its future imperial structure.
- 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: Gazi Triple: [Gaziantep, receivedTitle, Gazi]
Generated description
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gazi Target entity description: Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
A.
Mustafa
Mustafa is the given birth name of Mustafa Kemal Atatürk, the founder and first president of the Republic of Turkey.
-
B.
Giray
The Giray were the hereditary ruling dynasty of the Crimean Khanate, a prominent Turkic-Mongol royal house that claimed descent from Genghis Khan.
-
C.
Eskandar
Eskandar is a Persian and Arabic form of the name Alexander, commonly used in historical and literary contexts to refer to Alexander the Great.
-
D.
Atakule
Atakule is a prominent observation and communications tower in Ankara, Turkey, known for its panoramic city views and revolving restaurant.
-
E.
Orhan
Orhan was the second ruler of the early Ottoman state who significantly expanded its territories in northwestern Anatolia and laid foundations for its future imperial structure.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab7c139c8190b6d75661b5138d89 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d93af548190818c14a370e0914a |
completed | March 3, 2026, 11:24 p.m. |
| NEDg | Description generation | batch_69a781f5536c81908175d58b6b75adba |
completed | March 4, 2026, 12:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7860e656c8190a08a9999662ba1f1 |
completed | March 4, 2026, 1:08 a.m. |
Created at: March 1, 2026, 7:38 p.m.