Triple
T3493426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lapland |
E73789
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Levi
Levi is a popular ski resort and tourist destination in Finnish Lapland, known for its extensive slopes, winter sports, and vibrant holiday village.
|
E363786
|
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: Levi | Statement: [Lapland, contains, Levi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Levi Context triple: [Lapland, contains, Levi]
-
A.
Levi
Levi is the surname of Primo Levi, the renowned Italian Jewish chemist and writer best known for his memoirs about surviving the Auschwitz concentration camp.
-
B.
Levi
Levi is a biblical patriarch, one of the twelve sons of Jacob and ancestor of the Israelite tribe of Levi, traditionally associated with priestly duties.
-
C.
Pepe Jeans
Pepe Jeans is a British denim and casualwear fashion brand known for its trendy jeans and youthful, urban style.
-
D.
Levi's
Levi's is an iconic American denim and apparel brand best known for pioneering blue jeans and casual wear worldwide.
-
E.
Truman Belt
Truman Belt was a person significant enough in local history that the community of Beltsville, Maryland, was named in his honor.
- 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: Levi Triple: [Lapland, contains, Levi]
Generated description
Levi is a popular ski resort and tourist destination in Finnish Lapland, known for its extensive slopes, winter sports, and vibrant holiday village.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Levi Target entity description: Levi is a popular ski resort and tourist destination in Finnish Lapland, known for its extensive slopes, winter sports, and vibrant holiday village.
-
A.
Levi
Levi is the surname of Primo Levi, the renowned Italian Jewish chemist and writer best known for his memoirs about surviving the Auschwitz concentration camp.
-
B.
Levi
Levi is a biblical patriarch, one of the twelve sons of Jacob and ancestor of the Israelite tribe of Levi, traditionally associated with priestly duties.
-
C.
Pepe Jeans
Pepe Jeans is a British denim and casualwear fashion brand known for its trendy jeans and youthful, urban style.
-
D.
Levi's
Levi's is an iconic American denim and apparel brand best known for pioneering blue jeans and casual wear worldwide.
-
E.
Truman Belt
Truman Belt was a person significant enough in local history that the community of Beltsville, Maryland, was named in his honor.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbad51648190b756ad621d6d7df0 |
completed | March 8, 2026, 6:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373c23b188190a927d793b03192dc |
completed | March 13, 2026, 2:17 a.m. |
| NEDg | Description generation | batch_69b377a690348190a765b021bbbc820c |
completed | March 13, 2026, 2:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3781aaab48190a497a0929966ec12 |
completed | March 13, 2026, 2:36 a.m. |
Created at: March 8, 2026, 3:18 p.m.