Triple
T10478739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRIA |
E247114
|
entity |
| Predicate | successor |
P78
|
FINISHED |
| Object | INRIA |
E265286
|
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: INRIA | Statement: [IRIA, successor, INRIA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: INRIA Context triple: [IRIA, successor, INRIA]
-
A.
INRIA
chosen
INRIA is the French national research institute dedicated to computer science and applied mathematics, known for its leading contributions to digital science and technology.
-
B.
Grenoble INP
Grenoble INP is a French public engineering and technology institute in Grenoble, renowned for its network of specialized engineering schools and strong emphasis on research and innovation.
-
C.
INSA Lyon
INSA Lyon is a leading French grande école and engineering school located near Lyon, renowned for its strong research activity and multidisciplinary engineering programs.
-
D.
INSA Rennes
INSA Rennes is a leading French public engineering school located in Rennes, specializing in science and technology education and research.
-
E.
ENS Paris-Saclay
ENS Paris-Saclay is a prestigious French grande école that trains high-level researchers, academics, and professionals in science and humanities within the Université Paris-Saclay system.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5095a25708190bf34e3ca1491e003 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90db8b1288190bb6bb064cb0724e0 |
completed | April 10, 2026, 2:48 p.m. |
Created at: April 6, 2026, 12:21 p.m.