Triple
T10191180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seine-et-Oise |
E238036
|
entity |
| Predicate | successorDepartmentCode |
P6576
|
FINISHED |
| Object | 78 (Yvelines) |
—
|
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: 78 (Yvelines) | Statement: [Seine-et-Oise, successorDepartmentCode, 78 (Yvelines)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorDepartmentCode Context triple: [Seine-et-Oise, successorDepartmentCode, 78 (Yvelines)]
-
A.
successorAdministrativeUnit
chosen
Indicates that one administrative unit has officially replaced another in its governing or jurisdictional role.
-
B.
successorOfficeTo
Indicates that one office or position directly follows and replaces another in an official sequence or hierarchy.
-
C.
successorDivision
Indicates that one division is the organizational successor that continues or replaces the role, functions, or identity of another division.
-
D.
successorUnitIntegratedInto
Indicates that a subsequent or replacement unit has been incorporated into, or merged with, another unit as part of an organizational or structural succession.
-
E.
successorStation
Indicates that one station directly follows another in a sequence, such as along a transit line or route.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7eb1148190a2d175163685e233 |
completed | April 2, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:13 p.m.