Triple
T11326851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gouvy |
E268242
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Montleban
Montleban is a village in the municipality of Gouvy in the province of Luxembourg, Belgium.
|
E919308
|
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: Montleban | Statement: [Gouvy, hasSettlement, Montleban]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montleban Context triple: [Gouvy, hasSettlement, Montleban]
-
A.
Monteros
Monteros is a city in northwestern Argentina located in Tucumán Province, known for its agricultural production and proximity to the Aconquija mountain range.
-
B.
Mazunte
Mazunte is a small, laid-back beach town on Mexico’s Oaxacan coast, known for its sea turtle conservation center, eco-tourism, and scenic Pacific shoreline.
-
C.
Morrisania
Morrisania is a residential neighborhood in the South Bronx of New York City known for its historic role in the borough’s development and its predominantly working-class, diverse community.
-
D.
Marulanda
Marulanda is a small municipality and town located in the Caldas Department of Colombia, known for its rural Andean landscapes and agricultural economy.
-
E.
Moncalvo
Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
- 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: Montleban Triple: [Gouvy, hasSettlement, Montleban]
Generated description
Montleban is a village in the municipality of Gouvy in the province of Luxembourg, Belgium.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Montleban Target entity description: Montleban is a village in the municipality of Gouvy in the province of Luxembourg, Belgium.
-
A.
Monteros
Monteros is a city in northwestern Argentina located in Tucumán Province, known for its agricultural production and proximity to the Aconquija mountain range.
-
B.
Mazunte
Mazunte is a small, laid-back beach town on Mexico’s Oaxacan coast, known for its sea turtle conservation center, eco-tourism, and scenic Pacific shoreline.
-
C.
Morrisania
Morrisania is a residential neighborhood in the South Bronx of New York City known for its historic role in the borough’s development and its predominantly working-class, diverse community.
-
D.
Marulanda
Marulanda is a small municipality and town located in the Caldas Department of Colombia, known for its rural Andean landscapes and agricultural economy.
-
E.
Moncalvo
Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e2253881909518cad0f12ef612 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e52608b7348190875597513ca1a995 |
completed | April 19, 2026, 6:59 p.m. |
| NEDg | Description generation | batch_69e52c82b6108190aec9b6e9d726f803 |
completed | April 19, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e531c2a4b88190bb1efd57536bae9a |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:32 p.m.