Triple
T3333444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourg City |
E70084
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Hollerich
Hollerich is a district of Luxembourg City known for its mix of residential areas, nightlife, and transport connections, including a major railway station.
|
E349453
|
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: Hollerich | Statement: [Luxembourg City, hasDistrict, Hollerich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hollerich Context triple: [Luxembourg City, hasDistrict, Hollerich]
-
A.
Hemley
Hemley is a small rural village and civil parish located in the county of Suffolk in eastern England.
-
B.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
C.
Parlick
Parlick is a prominent hill in Lancashire, England, popular with walkers and paragliders and known for its sweeping views over the Forest of Bowland.
-
D.
Hollander
Hollander is a surname most prominently associated with English actor Tom Hollander, known for his versatile roles in film, television, and theatre.
-
E.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
- 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: Hollerich Triple: [Luxembourg City, hasDistrict, Hollerich]
Generated description
Hollerich is a district of Luxembourg City known for its mix of residential areas, nightlife, and transport connections, including a major railway station.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hollerich Target entity description: Hollerich is a district of Luxembourg City known for its mix of residential areas, nightlife, and transport connections, including a major railway station.
-
A.
Hemley
Hemley is a small rural village and civil parish located in the county of Suffolk in eastern England.
-
B.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
C.
Parlick
Parlick is a prominent hill in Lancashire, England, popular with walkers and paragliders and known for its sweeping views over the Forest of Bowland.
-
D.
Hollander
Hollander is a surname most prominently associated with English actor Tom Hollander, known for his versatile roles in film, television, and theatre.
-
E.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
- 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_69ad85a24f208190bcf83131bfed3521 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb194960081909333c855f06d8b03 |
completed | March 8, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b31a867cac81909ddde955c1752ab8 |
completed | March 12, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69b31c393f20819098d5761372d6a980 |
completed | March 12, 2026, 8:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3206be2748190874560701dc1ed18 |
completed | March 12, 2026, 8:22 p.m. |
Created at: March 8, 2026, 3:12 p.m.