Triple
T8435020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bagaran |
E199205
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Ayrarat |
E730928
|
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: Ayrarat | Statement: [Bagaran, historicalRegion, Ayrarat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayrarat Context triple: [Bagaran, historicalRegion, Ayrarat]
-
A.
Ayrarat
chosen
Ayrarat was the central and most important province of ancient Armenia, encompassing the Ararat plain and serving as a key political and cultural heartland.
-
B.
Ayaş
Ayaş is a small historic town and district in central Turkey known for its thermal springs and traditional architecture.
-
C.
Ayvansaray
Ayvansaray is a historic neighborhood on the Golden Horn in Istanbul, known for its old city walls, traditional wooden houses, and rich Byzantine and Ottoman heritage.
-
D.
Arak
Arak is a major industrial city in central Iran known for its manufacturing sector and strategic economic importance.
-
E.
Hashtgerd
Hashtgerd is a city in northern Iran that serves as an important urban center and gateway within Alborz Province, located west of Tehran.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd1a905ac8190b1015e1da9b16938 |
completed | March 31, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d71d9748190903ed97dde6d28f4 |
completed | April 2, 2026, 7:40 a.m. |
Created at: March 30, 2026, 6:08 p.m.