Triple
T13817873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marvdasht County |
E332063
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Marvdasht |
E581621
|
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: Marvdasht | Statement: [Marvdasht County, capital, Marvdasht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marvdasht Context triple: [Marvdasht County, capital, Marvdasht]
-
A.
Marvdasht
chosen
Marvdasht is a prominent city in Iran’s Fars Province, known for its proximity to the ancient ruins of Persepolis and its role as an agricultural and cultural center in the region.
-
B.
Meybod
Meybod is a historic desert city in central Iran known for its ancient mud-brick architecture, including caravanserais, fortresses, and traditional ice houses.
-
C.
Nahavand
Nahavand is a historic city in western Iran known as the site of a decisive 7th-century battle that contributed to the fall of the Sasanian Empire.
-
D.
Babolsar
Babolsar is a coastal city on the Caspian Sea in northern Iran, known as a regional tourist destination with beaches, a riverfront, and a popular seaside promenade.
-
E.
Sardasht
Sardasht is a Kurdish-populated city in Iran’s West Azerbaijan province, historically known for being one of the first civilian targets of large-scale chemical weapons attacks during the Iran–Iraq War.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0281bb988190803ee195f430b9c8 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7d20f548190a9f48e8c613abed4 |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:12 p.m.