Triple
T21748758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire Denis |
E536855
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Denis |
—
|
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: Denis | Statement: [Claire Denis, familyName, Denis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denis Context triple: [Claire Denis, familyName, Denis]
-
A.
Denis
chosen
Denis is a masculine given name of French origin, famously borne by the Enlightenment philosopher Denis Diderot.
-
B.
Denis
Denis was a key member of Les Nabis, a late 19th-century group of avant-garde French artists who helped pioneer Symbolism and modernist painting.
-
C.
Dennis
Dennis is a person or character notably linked to the concept or theme of pests, such as through pest control, infestation, or nuisance-related contexts.
-
D.
Dennis
Dennis is a masculine given name of Greek origin, commonly used in English-speaking countries.
-
E.
Dennis
Dennis is a central character in the film "Savages," involved in the violent and high-stakes world of drug trafficking.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a78bd908190b74e26ab1cc8788f |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:50 p.m.