Triple
T8597825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beykoz |
E203594
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Tokatköy
Tokatköy is a neighborhood located in the Beykoz district on the Asian side of Istanbul, Turkey.
|
E744717
|
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: Tokatköy | Statement: [Beykoz, contains, Tokatköy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokatköy Context triple: [Beykoz, contains, Tokatköy]
-
A.
Tikkakoski
Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
-
B.
Kokemäki
Kokemäki is a small town and municipality in the Satakunta region of western Finland, known for its location along the Kokemäenjoki River and its historical roots dating back to medieval times.
-
C.
Taivalkoski
Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Koivukylä
Koivukylä is a residential district in the city of Vantaa, Finland, known for its suburban housing, local services, and good rail connections to the Helsinki metropolitan area.
-
E.
Pöytyä
Pöytyä is a rural municipality in southwestern Finland known for its forests, agriculture, and small village communities.
- 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: Tokatköy Triple: [Beykoz, contains, Tokatköy]
Generated description
Tokatköy is a neighborhood located in the Beykoz district on the Asian side of Istanbul, Turkey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tokatköy Target entity description: Tokatköy is a neighborhood located in the Beykoz district on the Asian side of Istanbul, Turkey.
-
A.
Tikkakoski
Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
-
B.
Kokemäki
Kokemäki is a small town and municipality in the Satakunta region of western Finland, known for its location along the Kokemäenjoki River and its historical roots dating back to medieval times.
-
C.
Taivalkoski
Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Koivukylä
Koivukylä is a residential district in the city of Vantaa, Finland, known for its suburban housing, local services, and good rail connections to the Helsinki metropolitan area.
-
E.
Pöytyä
Pöytyä is a rural municipality in southwestern Finland known for its forests, agriculture, and small village communities.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46cacbe88190b95beeedc9f480b0 |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea8dd86d08190a7f8e674e16dd8b6 |
completed | April 2, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69cea9d0dad0819095134f6f8cafb4c0 |
completed | April 2, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ceaa7025388190a3f17aca46d4858e |
completed | April 2, 2026, 5:42 p.m. |
Created at: March 30, 2026, 6:24 p.m.