Triple
T33564462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valentinois |
E859716
|
entity |
| Predicate | associatedWithDepartmentCapital |
P17624
|
FINISHED |
| Object | Valence |
E8671
|
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: Valence | Statement: [Valentinois, associatedWithDepartmentCapital, Valence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithDepartmentCapital Context triple: [Valentinois, associatedWithDepartmentCapital, Valence]
-
A.
belongsToDepartmentCapitalRegion
Indicates that an entity is part of, or administratively assigned to, the capital region of a department.
-
B.
hasDepartmentCapital
Indicates that a department has a specific city designated as its capital.
-
C.
departmentalCapitalRole
Indicates that an entity serves in a capital-related role or function within a specific department.
-
D.
hasDepartmentCapitalNearby
Indicates that the subject entity has a departmental capital city located in close geographical proximity to it.
-
E.
capitalOfDepartment
chosen
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
- F. None of above.
Provenance (4 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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36270a9db48190ad26ec29ad4bf71f |
completed | June 20, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:40 a.m.