Triple
T12739573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karşıyaka |
E304452
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object | Alaybey |
E303194
|
NE FINISHED |
How this triple was built (2 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: Alaybey | Statement: [Karşıyaka, hasNeighbourhood, Alaybey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alaybey Context triple: [Karşıyaka, hasNeighbourhood, Alaybey]
-
A.
Alaybey
chosen
Alaybey is a neighborhood and tram stop area in the Karşıyaka district of İzmir, Turkey, integrated into the city's modern public transportation network.
-
B.
Sebkay
Sebkay was an obscure and possibly short-reigning pharaoh of Egypt’s 13th Dynasty during the Second Intermediate Period.
-
C.
Baskil
Baskil is a town and district in eastern Turkey known for its location within Elazığ Province and its predominantly rural, agricultural character.
-
D.
Abunayyan
Abunayyan is a prominent Saudi family name associated with influential figures in business and public life in Saudi Arabia.
-
E.
Aydin
Aydin is a given name used as a variant of Aidan, found in various cultures and spellings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69f67c8ff57c8190a935b5c9f4bb5aa3 |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 9, 2026, 5:26 p.m.