Triple
T18491648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Météore |
E451830
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | La Météore |
—
|
NE NERFINISHED |
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: La Météore | Statement: [La Météore, title, La Météore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Météore Context triple: [La Météore, title, La Météore]
-
A.
La Météore
chosen
La Météore is a scientific treatise by René Descartes that examines the nature and causes of meteorological phenomena such as clouds, rain, and halos.
-
B.
The Lightship
"The Lightship" is a 1985 drama film, based on a Siegfried Lenz novella, about a morally conflicted captain whose isolated vessel is taken over by criminals.
-
C.
The Barque of Dante
The Barque of Dante is a dramatic 1822 Romantic painting by Eugène Delacroix depicting Dante and Virgil crossing the infernal waters of the River Styx.
-
D.
Courthézon
Courthézon is a commune in southeastern France’s Vaucluse department, known for its historic village center, wine production in the Côtes du Rhône region, and proximity to Châteauneuf-du-Pape.
-
E.
A Disaster at Sea
A Disaster at Sea is a dramatic maritime painting by J.M.W. Turner, depicting a shipwreck amid stormy seas with his characteristic use of light and atmosphere.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e531dcac3c8190b2ebd129ca7f368d |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 10, 2026, 11:35 a.m.