Triple
T17848978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imera River |
E445743
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object |
Imera (Italian)
Imera is the Italian name for a historical river in Sicily, often associated with ancient Greek settlements and battles on the island.
|
E1291002
|
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: Imera (Italian) | Statement: [Imera River, hasNameInLanguage, Imera (Italian)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Imera (Italian) Context triple: [Imera River, hasNameInLanguage, Imera (Italian)]
-
A.
Ausa (Italian)
Ausa (Italian) is the Italian name for the Ausa River, a watercourse flowing through the Emilia-Romagna region of northern Italy.
-
B.
Risano (Italian)
Risano is the Italian name for the Rižana River, a small watercourse in southwestern Slovenia that flows into the Adriatic Sea near Koper.
-
C.
Muccino
Muccino is an Italian surname most notably associated with filmmaker Gabriele Muccino and his brother, actor-director Silvio Muccino.
-
D.
Talamello
Talamello is a small Italian town in the Emilia-Romagna region, known for its historic hilltop setting and production of traditional fossa cheese.
-
E.
Brezza
Brezza is a popular compact SUV produced by Maruti Suzuki for the Indian automotive market.
- 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: Imera (Italian) Triple: [Imera River, hasNameInLanguage, Imera (Italian)]
Generated description
Imera is the Italian name for a historical river in Sicily, often associated with ancient Greek settlements and battles on the island.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Imera (Italian) Target entity description: Imera is the Italian name for a historical river in Sicily, often associated with ancient Greek settlements and battles on the island.
-
A.
Ausa (Italian)
Ausa (Italian) is the Italian name for the Ausa River, a watercourse flowing through the Emilia-Romagna region of northern Italy.
-
B.
Risano (Italian)
Risano is the Italian name for the Rižana River, a small watercourse in southwestern Slovenia that flows into the Adriatic Sea near Koper.
-
C.
Muccino
Muccino is an Italian surname most notably associated with filmmaker Gabriele Muccino and his brother, actor-director Silvio Muccino.
-
D.
Talamello
Talamello is a small Italian town in the Emilia-Romagna region, known for its historic hilltop setting and production of traditional fossa cheese.
-
E.
Brezza
Brezza is a popular compact SUV produced by Maruti Suzuki for the Indian automotive market.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffd7e2c81909a42cc7ab64e7db9 |
completed | April 19, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a030705a2788190813a088556548a4e |
completed | May 12, 2026, 10:55 a.m. |
| NEDg | Description generation | batch_6a0307a17a4c81909a0b19b85a2d0adb |
completed | May 12, 2026, 10:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03080d46fc8190890000cfd0ede60e |
completed | May 12, 2026, 10:59 a.m. |
Created at: April 10, 2026, 10:16 a.m.