Triple
T20067214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorud |
E499637
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Dorūd |
—
|
NE NERFINISHED |
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: Dorūd | Statement: [Dorud, alternativeName, Dorūd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dorūd Context triple: [Dorud, alternativeName, Dorūd]
-
A.
Dorud
chosen
Dorud is a city in western Iran’s Lorestan Province, known as a regional rail junction and gateway to the surrounding Zagros mountain landscapes.
-
B.
Dorostol
Dorostol is the ancient name of the city now known as Silistra, a historically significant settlement on the Danube in northeastern Bulgaria.
-
C.
Hormuzd
Hormuzd is a masculine given name most notably borne by Hormuzd Rassam, a 19th-century Assyriologist and archaeologist known for his discoveries of ancient Mesopotamian artifacts.
-
D.
Rudabeh
Rudabeh is a legendary Persian princess and queen in the Shahnameh, renowned for her beauty, wisdom, and as the mother of the hero Rostam.
-
E.
Azarbarzin
Azarbarzin is a character from Persian epic tradition, known primarily as the son of the legendary hero Esfandiyar.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66379f2cc81908f13a7b216878f12 |
completed | April 20, 2026, 5:33 p.m. |
Created at: April 11, 2026, 3:39 p.m.