Triple
T22043975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillaume Postel |
E544712
|
entity |
| Predicate | educatedAt |
P5
|
FINISHED |
| Object | Collège Sainte-Barbe |
—
|
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: Collège Sainte-Barbe | Statement: [Guillaume Postel, educatedAt, Collège Sainte-Barbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Collège Sainte-Barbe Context triple: [Guillaume Postel, educatedAt, Collège Sainte-Barbe]
-
A.
Collège Sainte-Barbe
chosen
Collège Sainte-Barbe is a historic Parisian educational institution renowned for having educated prominent figures such as engineer Gustave Eiffel.
-
B.
Collège Saint-Pierre
Collège Saint-Pierre is a prominent Catholic educational institution in Haiti affiliated with the Diocese of Haiti.
-
C.
Collège Saint Marc
Collège Saint Marc is a prestigious French-language Catholic school in Alexandria, Egypt, known for educating many prominent figures from the region.
-
D.
Collège Sévigné
Collège Sévigné is a private, progressive secondary school in Paris known for its strong academic tradition and notable alumni.
-
E.
Collège Saint-Exupéry
Collège Saint-Exupéry is a French secondary school (collège) located in the commune of Saint-Leu-la-Forêt in northern France.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1282d5bb08190849d5084962bf3a5 |
completed | April 28, 2026, 9:35 p.m. |
Created at: April 16, 2026, 8:25 p.m.