Triple
T20976735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cluse de Pontarlier |
E516645
|
entity |
| Predicate | geologicalType |
P940
|
FINISHED |
| Object |
cluse
A cluse is a narrow transverse valley or gorge cut by a river through a mountain ridge or anticline, often forming a striking natural passage.
|
E1460315
|
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: cluse | Statement: [Cluse de Pontarlier, geologicalType, cluse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: cluse Context triple: [Cluse de Pontarlier, geologicalType, cluse]
-
A.
Clus
Clus is a historical name for the city of Kolozsvár (modern-day Cluj-Napoca) in Transylvania, Romania.
-
B.
CLU
CLU is an early high-level programming language from the 1970s that pioneered data abstraction, iterators, and exception handling, significantly influencing the design of later languages.
-
C.
CLU
CLU is a private liberal arts university in Thousand Oaks, California, known for its programs in business, education, and the humanities within a Lutheran tradition.
-
D.
LUCL
LUCL is a research and teaching institute at Leiden University specializing in linguistics and language-related studies.
-
E.
CLE
CLE is the standard abbreviation used for the Cleveland Monsters, a professional ice hockey team in the American Hockey League.
- 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: cluse Triple: [Cluse de Pontarlier, geologicalType, cluse]
Generated description
A cluse is a narrow transverse valley or gorge cut by a river through a mountain ridge or anticline, often forming a striking natural passage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: cluse Target entity description: A cluse is a narrow transverse valley or gorge cut by a river through a mountain ridge or anticline, often forming a striking natural passage.
-
A.
Clus
Clus is a historical name for the city of Kolozsvár (modern-day Cluj-Napoca) in Transylvania, Romania.
-
B.
CLU
CLU is an early high-level programming language from the 1970s that pioneered data abstraction, iterators, and exception handling, significantly influencing the design of later languages.
-
C.
CLU
CLU is a private liberal arts university in Thousand Oaks, California, known for its programs in business, education, and the humanities within a Lutheran tradition.
-
D.
LUCL
LUCL is a research and teaching institute at Leiden University specializing in linguistics and language-related studies.
-
E.
CLE
CLE is the standard abbreviation used for the Cleveland Monsters, a professional ice hockey team in the American Hockey League.
- 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_69e0b4fee5ac8190875fa9ceba1a5e5e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fba4a0dc819083b90795d26adfff |
completed | April 21, 2026, 4:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a092fbec34c819090f2a503633b7d3b |
completed | May 17, 2026, 3:02 a.m. |
| NEDg | Description generation | batch_6a093063be9c8190869f4e680aa7bff5 |
completed | May 17, 2026, 3:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0930c7e674819087c0c53cfdd1697f |
completed | May 17, 2026, 3:06 a.m. |
Created at: April 16, 2026, 1:47 p.m.