Triple
T15806439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nazilli |
E383227
|
entity |
| Predicate | railConnectionTo |
P13914
|
FINISHED |
| Object | Denizli |
E335876
|
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: Denizli | Statement: [Nazilli, railConnectionTo, Denizli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denizli Context triple: [Nazilli, railConnectionTo, Denizli]
-
A.
Denizli
chosen
Denizli is a major industrial and commercial city in western Turkey, known for its textile production and proximity to the famous Pamukkale travertine terraces.
-
B.
Gazipaşa
Gazipaşa is a coastal town and district in Antalya Province, southern Turkey, known for its Mediterranean beaches, agricultural production, and proximity to ancient ruins.
-
C.
Izmir
Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
-
D.
Çatalca
Çatalca is a rural district on the western outskirts of Istanbul, known for its forests, farmland, and historical fortifications forming part of the city’s traditional land defenses.
-
E.
Ayvacık
Ayvacık is a rural district and town in Turkey’s Black Sea region, located within Samsun Province and known for its natural landscapes and agricultural character.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52682548190998d8b6a08982877 |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe66d78c81908308fc16c8d4e19c |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:48 a.m.