Triple
T20067210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorud |
E499637
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Lorestan |
—
|
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: Lorestan | Statement: [Dorud, region, Lorestan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorestan Context triple: [Dorud, region, Lorestan]
-
A.
Lorestan Province
chosen
Lorestan Province is a mountainous region in western Iran known for its Lur population, rich history, and scenic landscapes of the Zagros Mountains.
-
B.
Khuzestan
Khuzestan is an oil-rich, ethnically diverse province in southwestern Iran, known historically as part of ancient Elam and as a major battleground during the Iran–Iraq War.
-
C.
Fars Province
Fars Province is a historically significant region in southwestern Iran, regarded as the cultural heartland of the Persian civilization and home to major ancient sites such as Persepolis and Pasargadae.
-
D.
Kermanshah Province
Kermanshah Province is a western region of Iran known for its mountainous terrain in the Zagros range, rich Kurdish culture, and important archaeological sites such as the Bisotun inscription.
-
E.
Markazi Province
Markazi Province is a central region of Iran known for its industrial cities and strategic location connecting major parts of the country.
- 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.