Triple
T16307763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grenoble INP – Institut d’ingénierie et de management |
E395966
|
entity |
| Predicate | hasCampus |
P116
|
FINISHED |
| Object | Valence |
E8671
|
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: Valence | Statement: [Grenoble INP – Institut d’ingénierie et de management, hasCampus, Valence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valence Context triple: [Grenoble INP – Institut d’ingénierie et de management, hasCampus, Valence]
-
A.
Valence
chosen
Valence is a historic city in southeastern France known as a key cultural and commercial center in the Drôme department.
-
B.
Vals
Vals is a Swiss Alpine village in the canton of Graubünden, renowned for its hot springs and Peter Zumthor’s iconic Therme Vals spa complex.
-
C.
Mood
"Mood" is a popular Afrobeats song by Nigerian artist Wizkid, known for its smooth, laid-back vibe and melodic delivery.
-
D.
Mood
Mood is an American hip hop group known for its underground, jazz-influenced sound and collaborations with producer Hi-Tek.
-
E.
Mood
"Mood" is a song by Canadian singer-songwriter Jessie Reyez that showcases her raw, emotionally charged style and confessional lyricism.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d776808190a7c9918477f07216 |
completed | April 17, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001fa517908190a29caa0156b1d1cd |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.