Triple
T864987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanzimat |
E18681
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Istanbul |
E4825
|
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: Istanbul | Statement: [Tanzimat, location, Istanbul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Istanbul Context triple: [Tanzimat, location, Istanbul]
-
A.
Istanbul
chosen
Istanbul is a transcontinental metropolis straddling Europe and Asia, renowned as Turkey’s cultural and economic hub and for its rich history as the former capital of the Byzantine and Ottoman Empires.
-
B.
Ankara
Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
-
C.
Trabzon
Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
-
D.
Izmir
Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
-
E.
Samsun
Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac6acc148190bcc00a1e939ace77 |
completed | March 1, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a0b0f548190a8ad0cf72cf23ebf |
completed | March 7, 2026, 1:37 p.m. |
Created at: March 1, 2026, 7:39 p.m.