Triple
T1918694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Iraq |
E40076
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Erbil |
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: Erbil | Statement: [Northern Iraq, containsCity, Erbil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erbil Context triple: [Northern Iraq, containsCity, Erbil]
-
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.
Mosul
Mosul is a major historic city in northern Iraq, known as a cultural and economic center on the Tigris River.
-
C.
Tikrit
Tikrit is a city in northern Iraq best known as the hometown of former president Saddam Hussein and a focal point in recent Iraqi history.
-
D.
Baghdad
Baghdad is the capital and largest city of Iraq, historically renowned as a major center of the Islamic Golden Age and a key cultural and economic hub of the Arab world.
-
E.
Sulaymaniyah
Sulaymaniyah is a major city in the Kurdistan Region of Iraq, known as a cultural and economic center with a diverse linguistic landscape.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb211eda88190865de7a0522a453d |
completed | March 7, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fce685081909038245bc0c1b4a6 |
completed | March 9, 2026, 1:18 a.m. |
Created at: March 4, 2026, 7:35 p.m.