Triple
T20067215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorud |
E499637
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Durud |
—
|
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: Durud | Statement: [Dorud, alternativeName, Durud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Durud Context triple: [Dorud, alternativeName, Durud]
-
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.
Durdar
Durdar is a village near Carlisle in Cumbria, England, known for being the site of Carlisle Racecourse.
-
C.
Babadag
Babadag is a small town in southeastern Romania known for its historical Ottoman influences and proximity to the Danube Delta.
-
D.
Gurdulù
Gurdulù is a comic, absent-minded squire in Italo Calvino’s novel "The Nonexistent Knight," known for his lack of self-awareness and contrast with the perfectly disciplined titular knight.
-
E.
Mudurnu
Mudurnu is a historic town and district in northwestern Turkey known for its well-preserved Ottoman architecture and traditional urban fabric.
- 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.