Triple
T31136134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Normandy |
E793645
|
entity |
| Predicate | composedOfDepartment |
P187389
|
FINISHED |
| Object | Seine-Maritime |
—
|
NE NERFINISHED |
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: Seine-Maritime | Statement: [Upper Normandy, composedOfDepartment, Seine-Maritime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: composedOfDepartment Context triple: [Upper Normandy, composedOfDepartment, Seine-Maritime]
-
A.
composedOfOffice
Indicates that something is made up of, or structurally includes, one or more offices as its constituent parts.
-
B.
worksInDepartment
Indicates that an entity is employed in and performs their job duties within a particular department.
-
C.
formedAsDepartment
Indicates that one entity was created or established as a department within another entity.
-
D.
basedInDepartment
Indicates that an entity operates or has its primary affiliation within a specific department.
-
E.
laterDepartment
Indicates that one department occurs or is considered after another in a defined ordering or sequence.
- F. None of above. chosen
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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb563a28d88190b28345c465c545f8 |
completed | May 6, 2026, 2:54 p.m. |
Created at: April 29, 2026, 9:05 p.m.