Triple
T15743392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Savona |
E381654
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object |
Ceriale
Ceriale is a coastal town and popular seaside resort in the Liguria region of northwestern Italy.
|
E1174237
|
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: Ceriale | Statement: [Province of Savona, containsAdministrativeTerritorialEntity, Ceriale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ceriale Context triple: [Province of Savona, containsAdministrativeTerritorialEntity, Ceriale]
-
A.
Centeno
Centeno is a Portuguese surname most notably associated with Mário Centeno, an economist and former finance minister of Portugal.
-
B.
Millet
Millet is a common French surname borne by several notable figures, including artists and sculptors.
-
C.
Millet
Millet is a group of small-seeded cereal grains widely cultivated for food and fodder, especially in semi-arid regions due to their drought resistance and short growing season.
-
D.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
-
E.
Farina
Farina is a memorable child character from the classic "Our Gang" (also known as "The Little Rascals") comedy film series, known for his expressive personality and comedic misadventures.
- 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: Ceriale Triple: [Province of Savona, containsAdministrativeTerritorialEntity, Ceriale]
Generated description
Ceriale is a coastal town and popular seaside resort in the Liguria region of northwestern Italy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ceriale Target entity description: Ceriale is a coastal town and popular seaside resort in the Liguria region of northwestern Italy.
-
A.
Centeno
Centeno is a Portuguese surname most notably associated with Mário Centeno, an economist and former finance minister of Portugal.
-
B.
Millet
Millet is a common French surname borne by several notable figures, including artists and sculptors.
-
C.
Millet
Millet is a group of small-seeded cereal grains widely cultivated for food and fodder, especially in semi-arid regions due to their drought resistance and short growing season.
-
D.
Farino
Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
-
E.
Farina
Farina is a memorable child character from the classic "Our Gang" (also known as "The Little Rascals") comedy film series, known for his expressive personality and comedic misadventures.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd97d6c8190b2fa6ca422bfe512 |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff83056aa0819098b757ed125e61fe |
completed | May 9, 2026, 6:55 p.m. |
| NEDg | Description generation | batch_69ff83ca33d08190816130bf2ea735df |
completed | May 9, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff846436e48190b711da134c9a3b81 |
completed | May 9, 2026, 7 p.m. |
Created at: April 10, 2026, 4:46 a.m.