Triple
T20540583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Université Paris-Sud |
E504318
|
entity |
| Predicate | campus |
P269
|
FINISHED |
| Object | Orsay |
—
|
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: Orsay | Statement: [Université Paris-Sud, campus, Orsay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orsay Context triple: [Université Paris-Sud, campus, Orsay]
-
A.
Orsay
chosen
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.
-
B.
Orsay
Orsay is a small uninhabited island off the southwest coast of Islay in Scotland, known for its historic lighthouse and rugged coastal scenery.
-
C.
Saclay
Saclay is a French commune in the Île-de-France region, known for hosting part of the Paris-Saclay research and university cluster.
-
D.
Place Jussieu
Place Jussieu is a public square in central Paris best known for hosting the Jussieu campus of Sorbonne University and several major scientific institutions.
-
E.
d'Orsay
d'Orsay is a French noble family name historically associated with aristocratic figures such as the 19th-century dandy and socialite Louis-Philippe, comte d'Orsay.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a29224f081908298d104161c5bb9 |
completed | April 20, 2026, 10:02 p.m. |
Created at: April 16, 2026, 11:37 a.m.