Triple
T7758909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Jutlandic Island |
E175967
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Grenen
Grenen is a scenic sandbar at the northern tip of Denmark where the Skagerrak and Kattegat seas meet, known for its unique coastal landscape and wildlife.
|
E686995
|
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: Grenen | Statement: [North Jutlandic Island, hasLandmark, Grenen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grenen Context triple: [North Jutlandic Island, hasLandmark, Grenen]
-
A.
Gruden
Gruden is a surname most prominently associated with Jon Gruden, a former NFL head coach and television analyst.
-
B.
Grenitote
Grenitote is a small settlement on the island of North Uist in Scotland’s Outer Hebrides.
-
C.
Vivarais
Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
-
D.
Letňany
Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
-
E.
Parugu
Parugu is a 2008 Telugu-language romantic drama film starring Allu Arjun, known for its emotional storyline and popular music.
- 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: Grenen Triple: [North Jutlandic Island, hasLandmark, Grenen]
Generated description
Grenen is a scenic sandbar at the northern tip of Denmark where the Skagerrak and Kattegat seas meet, known for its unique coastal landscape and wildlife.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grenen Target entity description: Grenen is a scenic sandbar at the northern tip of Denmark where the Skagerrak and Kattegat seas meet, known for its unique coastal landscape and wildlife.
-
A.
Gruden
Gruden is a surname most prominently associated with Jon Gruden, a former NFL head coach and television analyst.
-
B.
Grenitote
Grenitote is a small settlement on the island of North Uist in Scotland’s Outer Hebrides.
-
C.
Vivarais
Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
-
D.
Letňany
Letňany is a district in the northeastern part of Prague, Czech Republic, known for its residential areas, shopping centers, and transport links including a terminus of the city’s metro system.
-
E.
Parugu
Parugu is a 2008 Telugu-language romantic drama film starring Allu Arjun, known for its emotional storyline and popular music.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703de43d08190ac28bc17cd3e5ffa |
completed | March 27, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7cf538c8190aa86c27fff42efb0 |
completed | March 29, 2026, 6:33 a.m. |
| NEDg | Description generation | batch_69c8c8a18860819081a88f80544db83d |
completed | March 29, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8c900a28c819097449e8ceb373718 |
completed | March 29, 2026, 6:38 a.m. |
Created at: March 27, 2026, 4:09 p.m.