Triple
T18502536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hüseyin Pasha |
E452112
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Hüseyin
Hüseyin is a common Turkish male given name of Arabic origin, widely used in Turkey and other Muslim-majority regions.
|
E1329751
|
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: Hüseyin | Statement: [Hüseyin Pasha, givenName, Hüseyin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hüseyin Context triple: [Hüseyin Pasha, givenName, Hüseyin]
-
A.
Bekir
Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
-
B.
Abdüllatif
Abdüllatif is a Turkish male given name of Arabic origin, commonly used in Turkey and among Turkish-speaking communities.
-
C.
Celal
Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
-
D.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
-
E.
Kazım
Kazım is a Turkish given name most notably borne by Kazım Karabekir, a prominent Ottoman and early Republican-era military commander and statesman.
- 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: Hüseyin Triple: [Hüseyin Pasha, givenName, Hüseyin]
Generated description
Hüseyin is a common Turkish male given name of Arabic origin, widely used in Turkey and other Muslim-majority regions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hüseyin Target entity description: Hüseyin is a common Turkish male given name of Arabic origin, widely used in Turkey and other Muslim-majority regions.
-
A.
Bekir
Bekir is a common Turkish male given name of Arabic origin, often associated with early Islamic history and frequently borne by notable figures in Turkey.
-
B.
Abdüllatif
Abdüllatif is a Turkish male given name of Arabic origin, commonly used in Turkey and among Turkish-speaking communities.
-
C.
Celal
Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
-
D.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
-
E.
Kazım
Kazım is a Turkish given name most notably borne by Kazım Karabekir, a prominent Ottoman and early Republican-era military commander and statesman.
- 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c535908190bdc90c58fc5bdaf7 |
completed | April 19, 2026, 7:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0491672dc08190a09c74cb4e6cf06a |
completed | May 13, 2026, 2:57 p.m. |
| NEDg | Description generation | batch_6a04966f7b488190881d28e858ed7908 |
completed | May 13, 2026, 3:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0496ec05608190bfd16a0a36735255 |
completed | May 13, 2026, 3:21 p.m. |
Created at: April 10, 2026, 11:36 a.m.