Triple
T13432524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mashhad railway station |
E313646
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object |
Tabas
Tabas is a small desert city in central Iran known for its oasis landscapes, historical sites, and location along important regional transport routes.
|
E1040657
|
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: Tabas | Statement: [Mashhad railway station, connectsTo, Tabas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabas Context triple: [Mashhad railway station, connectsTo, Tabas]
-
A.
Taleqan
Taleqan is a small mountainous city in northern Iran known for its cool climate, natural landscapes, and traditional rural architecture.
-
B.
Bavanat
Bavanat is a small city in southern Iran known for its traditional rural landscapes, gardens, and location within the mountainous region of Fars Province.
-
C.
Minab
Minab is a city in southern Iran known for its agriculture, traditional markets, and proximity to the Persian Gulf.
-
D.
Margilan
Margilan is a historic city in eastern Uzbekistan renowned as a traditional center of silk production and trade along the Silk Road.
-
E.
Andimeshk
Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
- 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: Tabas Triple: [Mashhad railway station, connectsTo, Tabas]
Generated description
Tabas is a small desert city in central Iran known for its oasis landscapes, historical sites, and location along important regional transport routes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tabas Target entity description: Tabas is a small desert city in central Iran known for its oasis landscapes, historical sites, and location along important regional transport routes.
-
A.
Taleqan
Taleqan is a small mountainous city in northern Iran known for its cool climate, natural landscapes, and traditional rural architecture.
-
B.
Bavanat
Bavanat is a small city in southern Iran known for its traditional rural landscapes, gardens, and location within the mountainous region of Fars Province.
-
C.
Minab
Minab is a city in southern Iran known for its agriculture, traditional markets, and proximity to the Persian Gulf.
-
D.
Margilan
Margilan is a historic city in eastern Uzbekistan renowned as a traditional center of silk production and trade along the Silk Road.
-
E.
Andimeshk
Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed41a5481908800033303224adb |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7398da07081908c3eca6fc4213930 |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73b065818819095d26633fc682546 |
completed | May 3, 2026, 12:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73b8635888190b31035bc72676b9d |
completed | May 3, 2026, 12:11 p.m. |
Created at: April 9, 2026, 9:40 p.m.