Triple
T10380759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamedan Province |
E244633
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Famenin
Famenin is a small city in western Iran known for its agricultural economy and location within Hamedan Province.
|
E859460
|
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: Famenin | Statement: [Hamedan Province, hasCity, Famenin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Famenin Context triple: [Hamedan Province, hasCity, Famenin]
-
A.
Francene
Francene is a feminine given name, typically considered a variant of Francine and often associated with French origins meaning "from France" or "Frenchwoman."
-
B.
Leonessa
Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
-
C.
Fara
Fara is a character from A. E. van Vogt’s science fiction novel "The Weapon Shops of Isher," set in a far-future empire dominated by the powerful Isher dynasty and its enigmatic weapon dealers.
-
D.
Malèna
Malèna is a 2000 Italian coming-of-age drama film directed by Giuseppe Tornatore, known for its poignant portrayal of a beautiful war widow observed through the eyes of a young boy in World War II Sicily.
-
E.
Bahdini
Bahdini is a Northern Kurdish dialect spoken primarily in parts of Turkey and Iraq.
- 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: Famenin Triple: [Hamedan Province, hasCity, Famenin]
Generated description
Famenin is a small city in western Iran known for its agricultural economy and location within Hamedan Province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Famenin Target entity description: Famenin is a small city in western Iran known for its agricultural economy and location within Hamedan Province.
-
A.
Francene
Francene is a feminine given name, typically considered a variant of Francine and often associated with French origins meaning "from France" or "Frenchwoman."
-
B.
Leonessa
Leonessa is a historic mountain town in central Italy, known for its medieval architecture and scenic location in the Apennines.
-
C.
Fara
Fara is a character from A. E. van Vogt’s science fiction novel "The Weapon Shops of Isher," set in a far-future empire dominated by the powerful Isher dynasty and its enigmatic weapon dealers.
-
D.
Malèna
Malèna is a 2000 Italian coming-of-age drama film directed by Giuseppe Tornatore, known for its poignant portrayal of a beautiful war widow observed through the eyes of a young boy in World War II Sicily.
-
E.
Bahdini
Bahdini is a Northern Kurdish dialect spoken primarily in parts of Turkey and Iraq.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9921fa48190a874aa9a9e385b97 |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7958803e88190a7bbeda4f2c6f32c |
completed | April 9, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69d79784baa481909e57adda27578cc2 |
completed | April 9, 2026, 12:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7989f8dfc8190b1fe4429f7bb0283 |
completed | April 9, 2026, 12:16 p.m. |
Created at: April 6, 2026, 12:03 p.m.