Triple
T22842175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LNGS |
E566110
|
entity |
| Predicate | hasExperiment |
P37454
|
FINISHED |
| Object | GERDA |
—
|
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: GERDA | Statement: [LNGS, hasExperiment, GERDA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GERDA Context triple: [LNGS, hasExperiment, GERDA]
-
A.
GERDA
chosen
GERDA is a physics experiment at Italy’s Gran Sasso underground laboratory designed to search for neutrinoless double beta decay in germanium-76.
-
B.
Gerda
Gerda is the brave and devoted young heroine of Hans Christian Andersen’s fairy tale who embarks on a perilous journey to rescue her friend Kai from the Snow Queen.
-
C.
Gerti
Gerti is a central character in Elfriede Jelinek’s novel "Die Kinder der Toten," embodying the book’s haunting exploration of Austria’s repressed past and the lingering specters of history.
-
D.
GRETA
GRETA is an expert monitoring body of the Council of Europe that evaluates how member states implement measures to prevent and combat human trafficking and protect its victims.
-
E.
Gunta
Gunta is a given name most notably borne by Gunta Stölzl, a pioneering textile artist and the only female master at the Bauhaus school.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e855abc8190b9cf8cc515090a7f |
completed | April 29, 2026, 3:44 a.m. |
Created at: April 17, 2026, 3:35 p.m.