Triple
T9436072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentan |
E227509
|
entity |
| Predicate | regionCapitalOfDepartment |
P17624
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Argentan, regionCapitalOfDepartment, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionCapitalOfDepartment Context triple: [Argentan, regionCapitalOfDepartment, no]
-
A.
capitalOfDepartment
chosen
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
-
B.
geographicDirectionFromDepartmentCapital
Indicates that one location lies in a specified geographic direction relative to the capital city of a given administrative department.
-
C.
hasDepartmentCapital
Indicates that a department has a specific city designated as its capital.
-
D.
countryCapitalOfProvince
Indicates that a country serves as the capital or primary administrative center of a specified province.
-
E.
hasPopulationRankInDepartment
Indicates the relative position of an entity’s population size compared to other entities within the same department.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7ede1e148190b5793863a851c92c |
completed | April 1, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:50 p.m.