Triple
T551797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferney-Voltaire |
E11855
|
entity |
| Predicate | VoltaireResidenceFrom |
P4907
|
FINISHED |
| Object | 1759 |
—
|
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: 1759 | Statement: [Ferney-Voltaire, VoltaireResidenceFrom, 1759]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VoltaireResidenceFrom Context triple: [Ferney-Voltaire, VoltaireResidenceFrom, 1759]
-
A.
formerResidenceOf
chosen
Indicates that a location was once the place where a person or entity lived or was based, but is no longer their current residence.
-
B.
servedAsResidenceOf
Indicates that something functioned as the home or dwelling place of a particular person or group.
-
C.
fictionalResidence
Indicates that one entity is the place where another entity lives or is based within a fictional or imaginary context.
-
D.
hasNotableResident
Indicates that an entity is or has been a well-known or distinguished resident of a particular place or location.
-
E.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499047bd4819089ca8345f1b6e46c |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.