Triple
T15258153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourg City Hall |
E364700
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ville Haute |
E350581
|
NE FINISHED |
How this triple was built (2 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: Ville Haute | Statement: [Luxembourg City Hall, locatedIn, Ville Haute]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ville Haute Context triple: [Luxembourg City Hall, locatedIn, Ville Haute]
-
A.
Ville Haute
chosen
Ville Haute is the historic city-center district of Luxembourg City, known for its medieval fortifications, government buildings, and main shopping streets.
-
B.
Chaumont
Chaumont is a commune in northeastern France known as a local administrative and educational center, including hosting a campus of the University of Reims Champagne-Ardenne.
-
C.
Leudeville
Leudeville is a small commune in the Essonne department of the Île-de-France region in northern France.
-
D.
Orleans
Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
-
E.
Orleans
Orleans is a white grape variety used in European wine production, historically cultivated in regions such as Germany and Central Europe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084d11148190919eef8e55569bb9 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5f9a0708190bc429692788a63d7 |
completed | May 9, 2026, 7:44 a.m. |
Created at: April 10, 2026, 3:13 a.m.