Triple
T14458834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valentano |
E358528
|
entity |
| Predicate | bordersWith |
P224
|
FINISHED |
| Object |
Latera
Latera is a small municipality in the province of Viterbo in Italy’s Lazio region, known for its medieval hilltop setting near Lake Bolsena.
|
E1100358
|
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: Latera | Statement: [Valentano, bordersWith, Latera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Latera Context triple: [Valentano, bordersWith, Latera]
-
A.
Landana
Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
-
B.
Latorica
Latorica is a river in Central Europe that flows through western Ukraine and eastern Slovakia, forming part of the Tisza River basin.
-
C.
Parea
Parea is a small coastal village on the island of Huahine in French Polynesia, known for its tranquil beaches and traditional Polynesian atmosphere.
-
D.
Latavra
Latavra is a Georgian opera by composer Zakharia Paliashvili, known for its incorporation of Georgian folk themes and national musical style.
-
E.
Tamasopo
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
- 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: Latera Triple: [Valentano, bordersWith, Latera]
Generated description
Latera is a small municipality in the province of Viterbo in Italy’s Lazio region, known for its medieval hilltop setting near Lake Bolsena.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Latera Target entity description: Latera is a small municipality in the province of Viterbo in Italy’s Lazio region, known for its medieval hilltop setting near Lake Bolsena.
-
A.
Landana
Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
-
B.
Latorica
Latorica is a river in Central Europe that flows through western Ukraine and eastern Slovakia, forming part of the Tisza River basin.
-
C.
Parea
Parea is a small coastal village on the island of Huahine in French Polynesia, known for its tranquil beaches and traditional Polynesian atmosphere.
-
D.
Latavra
Latavra is a Georgian opera by composer Zakharia Paliashvili, known for its incorporation of Georgian folk themes and national musical style.
-
E.
Tamasopo
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91aabebc819097eb61b2d81c9a91 |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd64935d8081908e5b0e80027948e0 |
completed | May 8, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_69fd65cf06308190bf7b6463bc109542 |
completed | May 8, 2026, 4:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd66476ab88190b2d410ced33ce34b |
completed | May 8, 2026, 4:27 a.m. |
Created at: April 10, 2026, 1:19 a.m.