Triple
T6020473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fars |
E134049
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object |
Marvdasht
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.
|
E581621
|
NE FINISHED |
How this triple was built (4 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: [Fars, majorCity, Marvdasht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marvdasht Context triple: [Fars, majorCity, Marvdasht]
-
A.
Mazanderani
Mazanderani is a Northwestern Iranian language spoken along Iran’s Caspian Sea coast, particularly in Mazandaran Province.
-
B.
Meshginshahr
Meshginshahr is a city in northwestern Iran known for its proximity to Mount Sabalan and its hot springs.
-
C.
Kashan
Kashan is an Iranian city renowned for its rich history, traditional architecture, and production of high-quality Persian carpets.
-
D.
Sadabad
Sadabad is a town located in India’s culturally significant Braj region, traditionally associated with the life of Lord Krishna.
-
E.
Khorramabad
Khorramabad is a city in western Iran and the capital of Lorestan Province, known for its mountainous surroundings and historical sites such as Falak-ol-Aflak Castle.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Marvdasht Triple: [Fars, majorCity, Marvdasht]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marvdasht Target entity description: 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.
-
A.
Mazanderani
Mazanderani is a Northwestern Iranian language spoken along Iran’s Caspian Sea coast, particularly in Mazandaran Province.
-
B.
Meshginshahr
Meshginshahr is a city in northwestern Iran known for its proximity to Mount Sabalan and its hot springs.
-
C.
Kashan
Kashan is an Iranian city renowned for its rich history, traditional architecture, and production of high-quality Persian carpets.
-
D.
Sadabad
Sadabad is a town located in India’s culturally significant Braj region, traditionally associated with the life of Lord Krishna.
-
E.
Khorramabad
Khorramabad is a city in western Iran and the capital of Lorestan Province, known for its mountainous surroundings and historical sites such as Falak-ol-Aflak Castle.
- F. None of above. chosen
Provenance (5 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fba86a48190984e95d5adf7c7f1 |
completed | March 22, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c518c29dfc8190a55a54fbe6608dd2 |
completed | March 26, 2026, 11:30 a.m. |
| NEDg | Description generation | batch_69c51dac60ec8190a2f72913fdd301ca |
completed | March 26, 2026, 11:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c51e0b131c8190a2a9c29ace182c27 |
completed | March 26, 2026, 11:52 a.m. |
Created at: March 22, 2026, 4:07 p.m.