Triple
T2422195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frédéric Passy |
E53442
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Passy |
E89169
|
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: Passy | Statement: [Frédéric Passy, familyName, Passy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Passy Context triple: [Frédéric Passy, familyName, Passy]
-
A.
Passy
chosen
Passy is a Paris Métro station in the 16th arrondissement, serving Line 6 near the Trocadéro and the Seine.
-
B.
Mulhouse
Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
-
C.
Gonesse
Gonesse is a commune in the northeastern suburbs of Paris, France, known historically as a rural town and now as part of the greater Paris metropolitan area.
-
D.
Thoiry
Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
E.
Passy, Haute-Savoie
Passy, Haute-Savoie is a commune in the French Alps best known for its scenic mountain setting and as the place where Nobel Prize–winning scientist Marie Curie died.
- 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_69ab495c44d48190b7235b23719bc3f6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc971093481909c8924d58187860c |
completed | March 7, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf5b1bb8819095920d702c180d3f |
completed | March 9, 2026, 12:38 p.m. |
Created at: March 6, 2026, 9:42 p.m.