Triple
T17631240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlas linguistique de la France |
E429979
|
entity |
| Predicate | numberOfMaps |
P107897
|
FINISHED |
| Object | 1920 |
—
|
LITERAL 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: 1920 | Statement: [Atlas linguistique de la France, numberOfMaps, 1920]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMaps Context triple: [Atlas linguistique de la France, numberOfMaps, 1920]
-
A.
laterEditionApproximateNumberOfMaps
Indicates that a later edition of a work contains approximately the specified number of maps.
-
B.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
-
C.
numberOfMapsInFirstEdition
chosen
Indicates the quantity of maps contained in the first edition of a given work or publication.
-
D.
multiplayerMapCountAtLaunch
Indicates the number of multiplayer maps that are available when the game is first launched.
-
E.
numberOfMarkers
Indicates the quantity or count of markers associated with a given entity or context.
- F. None of above.
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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dc192dc8190854f1fe5d5ed696a |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:52 a.m.