Triple
T6656445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis de France |
E150957
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Fontainebleau |
E25615
|
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: Fontainebleau | Statement: [Louis de France, birthPlace, Fontainebleau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fontainebleau Context triple: [Louis de France, birthPlace, Fontainebleau]
-
A.
Fontainebleau, France
chosen
Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
-
B.
Palaiseau
Palaiseau is a suburban commune in the southern outskirts of Paris, France, known for hosting major scientific and engineering institutions.
-
C.
Trappes
Trappes is a suburban commune in north-central France, located in the Yvelines department within the Île-de-France region near Paris.
-
D.
Saint-Germain-en-Laye
Saint-Germain-en-Laye is a historic town in the western suburbs of Paris, France, known for its royal château and long association with the French monarchy.
-
E.
Neuilly-sur-Seine
Neuilly-sur-Seine is an affluent suburban commune just west of central Paris, known for its upscale residential neighborhoods and proximity to major business districts like La Défense.
- 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b06dbbf88190b39564a688c25a24 |
completed | March 27, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6ef028ccc8190a56395075c9aabf7 |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2:01 p.m.