Triple
T3312696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molise |
E69608
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Larino
Larino is a historic town in the Molise region of southern Italy, known for its Roman amphitheater, medieval architecture, and traditional festivals.
|
E345745
|
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: Larino | Statement: [Molise, containsTown, Larino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larino Context triple: [Molise, containsTown, Larino]
-
A.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
B.
Serón
Serón is a small rural settlement located in the Río Hurtado area of northern Chile, known for its Andean landscapes and agricultural surroundings.
-
C.
El Porvenir
El Porvenir is a small Caribbean coastal town in Panama that serves as the administrative center of the indigenous Guna Yala comarca.
-
D.
Avellaneda
Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
-
E.
Carabajal
Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
- 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: Larino Triple: [Molise, containsTown, Larino]
Generated description
Larino is a historic town in the Molise region of southern Italy, known for its Roman amphitheater, medieval architecture, and traditional festivals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Larino Target entity description: Larino is a historic town in the Molise region of southern Italy, known for its Roman amphitheater, medieval architecture, and traditional festivals.
-
A.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
B.
El Porvenir
El Porvenir is a small Caribbean coastal town in Panama that serves as the administrative center of the indigenous Guna Yala comarca.
-
C.
Serón
Serón is a small rural settlement located in the Río Hurtado area of northern Chile, known for its Andean landscapes and agricultural surroundings.
-
D.
Avellaneda
Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
-
E.
Carabajal
Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0eddf488190b7f05b3903b96d4b |
completed | March 8, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3f3ece08190b488be792d57a653 |
completed | March 12, 2026, 5:12 p.m. |
| NEDg | Description generation | batch_69b2fa431f4c819088c6e0afd4f2f774 |
completed | March 12, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2fe1d4f9c8190a8d4f1206c551671 |
completed | March 12, 2026, 5:55 p.m. |
Created at: March 8, 2026, 3:11 p.m.