Triple
T2042620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syr Darya |
E44777
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object |
Seyhun
Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
|
E228152
|
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: Seyhun | Statement: [Syr Darya, historicalName, Seyhun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seyhun Context triple: [Syr Darya, historicalName, Seyhun]
-
A.
Eyüp
Eyüp is a historic district on Istanbul’s Golden Horn, known for its important Ottoman-era mosque complex and traditional neighborhoods.
-
B.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
C.
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.
-
D.
Malhun Hatun
Malhun Hatun was a prominent figure in early Ottoman history, traditionally regarded as one of the wives of Osman I and the mother of his successor, Orhan.
-
E.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
- 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: Seyhun Triple: [Syr Darya, historicalName, Seyhun]
Generated description
Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seyhun Target entity description: Seyhun is the historical name used in Islamic and Central Asian sources for the Syr Darya River, one of the major rivers of Central Asia.
-
A.
Eyüp
Eyüp is a historic district on Istanbul’s Golden Horn, known for its important Ottoman-era mosque complex and traditional neighborhoods.
-
B.
Gazi
Gazi is an honorific title in Turkey, historically bestowed for distinguished military valor and sacrifice in war.
-
C.
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.
-
D.
Malhun Hatun
Malhun Hatun was a prominent figure in early Ottoman history, traditionally regarded as one of the wives of Osman I and the mother of his successor, Orhan.
-
E.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
- 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_69a889159ec481908f9e4472d9f480c7 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb95587348190bb5719faeaf0aa5d |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1ffbbf948190a89932013b463f85 |
completed | March 9, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69ae20946a288190a3bd2a19e3608e86 |
completed | March 9, 2026, 1:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae2109d17c819094a298a822064052 |
completed | March 9, 2026, 1:23 a.m. |
Created at: March 4, 2026, 7:39 p.m.