Triple
T13121901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menemen |
E311742
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Aliağa |
E309020
|
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: Aliağa | Statement: [Menemen, adjacentTo, Aliağa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aliağa Context triple: [Menemen, adjacentTo, Aliağa]
-
A.
Aliağa
chosen
Aliağa is a coastal industrial district and port town in İzmir Province, Turkey, known for its petrochemical facilities and ship-breaking yards.
-
B.
Yalıköy
Yalıköy is a neighborhood in the Beykoz district of Istanbul, Turkey, known for its residential character and proximity to the Bosphorus.
-
C.
Torbalı
Torbalı is a district and rapidly growing suburban area of İzmir, Turkey, known for its industrial zones and connection to the city via the İZBAN commuter rail system.
-
D.
Kemalpaşa
Kemalpaşa is a district and town in western Turkey known for its cherry production and proximity to the city of İzmir.
-
E.
Ortaca
Ortaca is a town and district in southwestern Turkey known for its proximity to popular Aegean and Mediterranean coastal resorts and natural attractions.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819840b881909b76022b4c4dcaed |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdee8d1408190942ff455e7b1b6e2 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 9:06 p.m.