Triple
T2488108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nebrodi |
E55975
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object |
Monte Soro
Monte Soro is a prominent mountain peak in northeastern Sicily, Italy, known as the highest summit of the Nebrodi mountain range.
|
E271365
|
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: Monte Soro | Statement: [Nebrodi, highestPoint, Monte Soro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monte Soro Context triple: [Nebrodi, highestPoint, Monte Soro]
-
A.
Monte Gordo
Monte Gordo is a popular seaside resort town in Portugal’s Algarve region, known for its wide sandy beaches and tourism-focused amenities.
-
B.
Monte Toro
Monte Toro is the tallest mountain on the Spanish island of Menorca, known for its panoramic views and a sanctuary at its summit.
-
C.
Monte de El Pardo
Monte de El Pardo is a large protected forested area and royal hunting estate on the outskirts of Madrid, Spain, known for its Mediterranean woodland and rich wildlife.
-
D.
Cerro Huelén
Cerro Huelén is the historic hill in central Santiago, Chile, now known as Cerro Santa Lucía, notable as a key colonial landmark and urban park.
-
E.
Monchique
Monchique is a mountainous spa town in southern Portugal known for its lush forests, thermal springs, and panoramic views over the Algarve region.
- 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: Monte Soro Triple: [Nebrodi, highestPoint, Monte Soro]
Generated description
Monte Soro is a prominent mountain peak in northeastern Sicily, Italy, known as the highest summit of the Nebrodi mountain range.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monte Soro Target entity description: Monte Soro is a prominent mountain peak in northeastern Sicily, Italy, known as the highest summit of the Nebrodi mountain range.
-
A.
Monte Gordo
Monte Gordo is a popular seaside resort town in Portugal’s Algarve region, known for its wide sandy beaches and tourism-focused amenities.
-
B.
Monte Toro
Monte Toro is the tallest mountain on the Spanish island of Menorca, known for its panoramic views and a sanctuary at its summit.
-
C.
Monte de El Pardo
Monte de El Pardo is a large protected forested area and royal hunting estate on the outskirts of Madrid, Spain, known for its Mediterranean woodland and rich wildlife.
-
D.
Cerro Huelén
Cerro Huelén is the historic hill in central Santiago, Chile, now known as Cerro Santa Lucía, notable as a key colonial landmark and urban park.
-
E.
Monchique
Monchique is a mountainous spa town in southern Portugal known for its lush forests, thermal springs, and panoramic views over the Algarve region.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd179c44881909cd6c7626cadaf10 |
completed | March 7, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af17bca6f88190a63672fb3372f0be |
completed | March 9, 2026, 6:55 p.m. |
| NEDg | Description generation | batch_69af1b7224488190bf896b2c77c3ba0a |
completed | March 9, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af1c7b0f088190870b2ed18756b0d5 |
completed | March 9, 2026, 7:16 p.m. |
Created at: March 6, 2026, 9:45 p.m.