Triple
T12739578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karşıyaka |
E304452
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object |
Bahçelievler
Bahçelievler is a residential neighborhood located within the Karşıyaka district of İzmir, Turkey.
|
E1009755
|
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: Bahçelievler | Statement: [Karşıyaka, hasNeighbourhood, Bahçelievler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bahçelievler Context triple: [Karşıyaka, hasNeighbourhood, Bahçelievler]
-
A.
Bahçelievler
Bahçelievler is a densely populated residential and commercial district on the European side of Istanbul, Turkey.
-
B.
Avcılar
Avcılar is a district on the European side of Istanbul, Turkey, known for its residential areas, university campus, and location along the Marmara Sea.
-
C.
Sultanbeyli
Sultanbeyli is a densely populated, predominantly residential district on the Asian side of Istanbul, known for its rapid urbanization and working-class character.
-
D.
Bağcılar
Bağcılar is a densely populated working- and middle-class district on Istanbul’s European side, known as a major residential and transportation hub within the city.
-
E.
Doğanşehir
Doğanşehir is a district and town in eastern Turkey known for its agricultural production and location within Malatya Province.
- 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: Bahçelievler Triple: [Karşıyaka, hasNeighbourhood, Bahçelievler]
Generated description
Bahçelievler is a residential neighborhood located within the Karşıyaka district of İzmir, Turkey.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bahçelievler Target entity description: Bahçelievler is a residential neighborhood located within the Karşıyaka district of İzmir, Turkey.
-
A.
Bahçelievler
Bahçelievler is a densely populated residential and commercial district on the European side of Istanbul, Turkey.
-
B.
Avcılar
Avcılar is a district on the European side of Istanbul, Turkey, known for its residential areas, university campus, and location along the Marmara Sea.
-
C.
Sultanbeyli
Sultanbeyli is a densely populated, predominantly residential district on the Asian side of Istanbul, known for its rapid urbanization and working-class character.
-
D.
Bağcılar
Bağcılar is a densely populated working- and middle-class district on Istanbul’s European side, known as a major residential and transportation hub within the city.
-
E.
Doğanşehir
Doğanşehir is a district and town in eastern Turkey known for its agricultural production and location within Malatya Province.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9646dfc908190bc398935d1d23537 |
completed | April 10, 2026, 8:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a53e9fa08190805d55e9fcf7e79f |
completed | May 3, 2026, 1:30 a.m. |
| NEDg | Description generation | batch_69f6a68978008190a9d8695b09a8cb3a |
completed | May 3, 2026, 1:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6a8a31264819082c1ce67eaa529cc |
completed | May 3, 2026, 1:45 a.m. |
Created at: April 9, 2026, 5:26 p.m.