Triple
T5792469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlottenlund Palace |
E128426
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Charlottenlund
Charlottenlund is a suburban district north of central Copenhagen, Denmark, known for its affluent residential areas, coastal location, and historic royal palace and park.
|
E546438
|
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: Charlottenlund | Statement: [Charlottenlund Palace, locatedIn, Charlottenlund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlottenlund Context triple: [Charlottenlund Palace, locatedIn, Charlottenlund]
-
A.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
B.
Hillerød
Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
-
C.
Ringsted
Ringsted is a historic market town and transport hub located in the central part of the Danish island of Zealand.
-
D.
Høje Taastrup
Høje Taastrup is a major suburban railway and transport hub in the western part of the Copenhagen metropolitan area.
-
E.
Ennore
Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
- 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: Charlottenlund Triple: [Charlottenlund Palace, locatedIn, Charlottenlund]
Generated description
Charlottenlund is a suburban district north of central Copenhagen, Denmark, known for its affluent residential areas, coastal location, and historic royal palace and park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charlottenlund Target entity description: Charlottenlund is a suburban district north of central Copenhagen, Denmark, known for its affluent residential areas, coastal location, and historic royal palace and park.
-
A.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
-
B.
Hillerød
Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
-
C.
Ringsted
Ringsted is a historic market town and transport hub located in the central part of the Danish island of Zealand.
-
D.
Høje Taastrup
Høje Taastrup is a major suburban railway and transport hub in the western part of the Copenhagen metropolitan area.
-
E.
Ennore
Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a5870b88190bbfaac2782635128 |
completed | March 22, 2026, 5:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09824c7f0819095565e0f29b3a508 |
completed | March 23, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69c098a0325c81909a1326b94e40ed50 |
completed | March 23, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c09943deec819085992c4e44050a34 |
completed | March 23, 2026, 1:37 a.m. |
Created at: March 22, 2026, 3:51 p.m.