Triple
T3231648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erbil |
E67752
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object | Arbīl |
E67752
|
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: Arbīl | Statement: [Erbil, historicalName, Arbīl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arbīl Context triple: [Erbil, historicalName, Arbīl]
-
A.
Erbil
chosen
Erbil is the capital and largest city of the Kurdistan Region in northern Iraq, known as one of the world’s oldest continuously inhabited urban centers.
-
B.
Duhok
Duhok is a city in the Kurdistan Region of Iraq, known as a growing cultural and economic center surrounded by mountains near the Turkish and Syrian borders.
-
C.
Mosul
Mosul is a major historic city in northern Iraq, known as a cultural and economic center on the Tigris River.
-
D.
Kirkuk
Kirkuk is a historically significant, oil-rich and ethnically diverse city in northern Iraq that has long been a focal point of political and territorial disputes.
-
E.
Diyarbakır
Diyarbakır is a major historic city in southeastern Turkey, renowned for its extensive black basalt city walls and rich Kurdish and Mesopotamian heritage.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaed99d2c8190950fa883ec6f1f8e |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33411537081908624477fca92296d |
completed | March 12, 2026, 9:45 p.m. |
Created at: March 8, 2026, 3:08 p.m.