Triple
T4237168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gallura |
E94721
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Aglientu
Aglientu is a small coastal town and comune in the Gallura region of northern Sardinia, Italy, known for its scenic beaches and rural landscapes.
|
E423869
|
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: Aglientu | Statement: [Gallura, containsCity, Aglientu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aglientu Context triple: [Gallura, containsCity, Aglientu]
-
A.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
B.
Egencia
Egencia is a corporate travel management company that provides technology-driven solutions for booking and managing business travel worldwide.
-
C.
Zenta
Zenta is a historic town in northern Serbia, best known as the site of a decisive 1697 battle between the Habsburg Monarchy and the Ottoman Empire.
-
D.
Alberoni
Alberoni is an Italian surname most notably associated with Giulio Alberoni, an influential 18th-century cardinal and statesman.
-
E.
Adigeni
Adigeni is a small town in southern Georgia, serving as a local administrative and cultural center within the Samtskhe-Javakheti 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: Aglientu Triple: [Gallura, containsCity, Aglientu]
Generated description
Aglientu is a small coastal town and comune in the Gallura region of northern Sardinia, Italy, known for its scenic beaches and rural landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aglientu Target entity description: Aglientu is a small coastal town and comune in the Gallura region of northern Sardinia, Italy, known for its scenic beaches and rural landscapes.
-
A.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
B.
Egencia
Egencia is a corporate travel management company that provides technology-driven solutions for booking and managing business travel worldwide.
-
C.
Zenta
Zenta is a historic town in northern Serbia, best known as the site of a decisive 1697 battle between the Habsburg Monarchy and the Ottoman Empire.
-
D.
Alberoni
Alberoni is an Italian surname most notably associated with Giulio Alberoni, an influential 18th-century cardinal and statesman.
-
E.
Adigeni
Adigeni is a small town in southern Georgia, serving as a local administrative and cultural center within the Samtskhe-Javakheti 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e7589b48190a16e7ff29fb6a162 |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a86996f48190987d3ac234a9b7f4 |
completed | March 14, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69b5a9f58de48190b6f2f56804bc6d30 |
completed | March 14, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5aabd2080819091d65362cf02120b |
completed | March 14, 2026, 6:36 p.m. |
Created at: March 12, 2026, 11:05 p.m.