Triple
T678202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nijmegen |
E13123
|
entity |
| Predicate | twinCity |
P1072
|
FINISHED |
| Object | Gaziantep, Turkey |
E17791
|
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: Gaziantep, Turkey | Statement: [Nijmegen, twinCity, Gaziantep, Turkey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaziantep, Turkey Context triple: [Nijmegen, twinCity, Gaziantep, Turkey]
-
A.
Gaziantep
chosen
Gaziantep is a major city in southeastern Turkey known for its rich history, cultural heritage, and renowned pistachio-based cuisine, especially baklava.
-
B.
Konya
Konya is a major city in central Anatolia known for its rich Seljuk heritage and as the home of the Sufi mystic Rumi and the Whirling Dervishes.
-
C.
Samsun
Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
-
D.
Trabzon
Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
-
E.
Erzurum, Turkey
Erzurum, Turkey is a historic city in eastern Anatolia known for its Ottoman-era architecture, harsh winters, and role as a regional cultural and educational center.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a04e17088190943d54977eb3f83a |
completed | March 1, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a66d8f4a908190bc4cf5e1a6e46628 |
completed | March 3, 2026, 5:11 a.m. |
Created at: March 1, 2026, 7:36 p.m.