Triple
T1713764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German-speaking Community |
E37242
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lontzen
Lontzen is a municipality in eastern Belgium, located in the country’s German-speaking region near the border with Germany.
|
E192745
|
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: Lontzen | Statement: [German-speaking Community, contains, Lontzen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lontzen Context triple: [German-speaking Community, contains, Lontzen]
-
A.
Veltro
Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
-
B.
Lunan
Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
-
C.
Trezzini
Trezzini is an Italian-origin surname most notably associated with Domenico Trezzini, the Swiss-Italian architect who helped shape early 18th-century Saint Petersburg.
-
D.
Huelén
Huelén is the former indigenous name for Cerro Santa Lucía, a historic hill and urban park in central Santiago, Chile.
-
E.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
- 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: Lontzen Triple: [German-speaking Community, contains, Lontzen]
Generated description
Lontzen is a municipality in eastern Belgium, located in the country’s German-speaking region near the border with Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lontzen Target entity description: Lontzen is a municipality in eastern Belgium, located in the country’s German-speaking region near the border with Germany.
-
A.
Veltro
Veltro is the nickname of the Macchi C.205, an Italian World War II fighter aircraft renowned for its speed and agility.
-
B.
Lunan
Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
-
C.
Trezzini
Trezzini is an Italian-origin surname most notably associated with Domenico Trezzini, the Swiss-Italian architect who helped shape early 18th-century Saint Petersburg.
-
D.
Huelén
Huelén is the former indigenous name for Cerro Santa Lucía, a historic hill and urban park in central Santiago, Chile.
-
E.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa63174b3c8190bd2406c78407be28 |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ae10a048190b7a39e4fb4fbe224 |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad957adf1c8190b7c8656c1984f998 |
completed | March 8, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad97af6b388190b2af293599108df3 |
completed | March 8, 2026, 3:37 p.m. |
Created at: March 4, 2026, 7:30 p.m.