Triple
T21645907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Basel-Landschaft |
E534213
|
entity |
| Predicate | numberOfNotchesOnCrosier |
P145366
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [flag of Basel-Landschaft, numberOfNotchesOnCrosier, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNotchesOnCrosier Context triple: [flag of Basel-Landschaft, numberOfNotchesOnCrosier, 7]
-
A.
numberOfStationsOfTheCross
Indicates the total count of Stations of the Cross associated with a given subject.
-
B.
numberInStationsOfTheCross
Indicates the specific ordinal position that an event or scene occupies within the sequence of the Stations of the Cross.
-
C.
traditionalSideOfCross
Indicates the side of a cross that is considered the customary or historically recognized orientation in a given tradition.
-
D.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
-
E.
crossesIn
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5394c570819081dbbe7e0f98f7d3 |
completed | April 27, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:35 p.m.