Triple
T15862370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jussieu |
E384620
|
entity |
| Predicate | nearby |
P350
|
FINISHED |
| Object | Place Jussieu |
E254187
|
NE 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: Place Jussieu | Statement: [Jussieu, nearby, Place Jussieu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Place Jussieu Context triple: [Jussieu, nearby, Place Jussieu]
-
A.
Place Jussieu
chosen
Place Jussieu is a public square in central Paris best known for hosting the Jussieu campus of Sorbonne University and several major scientific institutions.
-
B.
Jussieu
Jussieu refers to members of the French Jussieu family of botanists, notably Antoine Laurent de Jussieu, who were pioneers in developing modern plant classification systems.
-
C.
Orsay
Orsay is a commune in the southern suburbs of Paris, France, known for hosting part of the Paris-Saclay University and several major scientific research institutions.
-
D.
Orsay
Orsay is a small uninhabited island off the southwest coast of Islay in Scotland, known for its historic lighthouse and rugged coastal scenery.
-
E.
Place de la Sorbonne
Place de la Sorbonne is a historic square in Paris’s Latin Quarter, known for its proximity to the Sorbonne University and its lively cafés and student atmosphere.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555c75688190aeae5bcf5bb92bb7 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb59ddc488190ae6b6913f85005f6 |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 4:50 a.m.