Triple
T4179610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mende |
E86560
|
entity |
| Predicate | departmentPopulationRank |
P25930
|
FINISHED |
| Object | largest town in Lozère department |
—
|
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: largest town in Lozère department | Statement: [Mende, departmentPopulationRank, largest town in Lozère department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentPopulationRank Context triple: [Mende, departmentPopulationRank, largest town in Lozère department]
-
A.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
B.
populationRankAfter
Indicates the relative position of an entity in a population-based ordering that comes after another entity’s population rank.
-
C.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
hasPopulationRankInRegion
chosen
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
-
E.
rankByPopulationInUS
Indicates the relative ordering of entities based on the size of their populations within the United States.
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:45 p.m.