Triple
T22234562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cimiez Cemetery |
E549556
|
entity |
| Predicate | hasNotableBurial |
P196
|
FINISHED |
| Object | Arman |
—
|
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: Arman | Statement: [Cimiez Cemetery, hasNotableBurial, Arman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arman Context triple: [Cimiez Cemetery, hasNotableBurial, Arman]
-
A.
Arman
chosen
Arman was a French-born American artist best known for his pioneering work in Nouveau Réalisme, particularly his accumulations and destructions of everyday objects as sculptural and conceptual art.
-
B.
Aramm
Aramm is a 2017 Tamil social drama film starring Nayanthara as a dedicated district collector tackling a village water crisis and systemic negligence.
-
C.
Arnish
Arnish is a small village located on the Isle of Raasay in the Inner Hebrides of Scotland.
-
D.
Armin
Armin is the given name of Armin Mueller-Stahl, a renowned German actor, painter, and former musician known for his work in both European and Hollywood cinema.
-
E.
Arleng
Arleng is an alternative name for the Karbi language spoken by the Karbi people of Northeast India.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf61504819093e70bee4c575d1c |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:38 p.m.