Triple
T7438123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charleville-Mézières |
E171671
|
entity |
| Predicate | RimbaudMuseumLocatedIn |
P37091
|
FINISHED |
| Object | old water mill on the Meuse |
—
|
LITERAL 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: old water mill on the Meuse | Statement: [Charleville-Mézières, RimbaudMuseumLocatedIn, old water mill on the Meuse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RimbaudMuseumLocatedIn Context triple: [Charleville-Mézières, RimbaudMuseumLocatedIn, old water mill on the Meuse]
-
A.
museumDedicatedToArtistLocation
Indicates that a museum, dedicated to a particular artist, is located at a specific place.
-
B.
famousArtworkLocatedIn
Indicates that a specific famous artwork is physically situated or displayed within a particular location or venue.
-
C.
hasMemorialMuseum
Indicates that a memorial museum is dedicated to, associated with, or established in honor of a particular entity.
-
D.
museumAt
Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
-
E.
hasMuseumAt
chosen
Indicates that a museum is located at or exists in a specified place or location.
- F. None of above.
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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.