Triple
T4699065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaucluse |
E104221
|
entity |
| Predicate | subprefecture |
P9697
|
FINISHED |
| Object | Apt |
E130575
|
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: Apt | Statement: [Vaucluse, subprefecture, Apt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apt Context triple: [Vaucluse, subprefecture, Apt]
-
A.
Apt
chosen
Apt is a historic market town in southeastern France’s Vaucluse department, known for its candied fruit production and Provençal charm.
-
B.
AAPT
AAPT is a professional organization dedicated to advancing the teaching and learning of physics at all educational levels.
-
C.
Debian
Debian is a widely used, community-driven Linux distribution known for its stability, extensive package repository, and role as the basis for many other operating systems such as Ubuntu.
-
D.
Flatpak
Flatpak is a cross-distribution Linux framework for building, distributing, and running sandboxed desktop applications.
-
E.
YUM
YUM is a command-line package management utility for RPM-based Linux distributions that automatically handles software installation, updates, and dependency resolution.
- 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_69bd43e9b88481908582103dcadff3d9 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63b57e1c8190962d97e4805974ed |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03c7469081908cf587b2356a4320 |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:17 p.m.