Triple
T37000424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Overkwartier van Gelre |
E915329
|
entity |
| Predicate | nonContiguous |
P29207
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Overkwartier van Gelre, nonContiguous, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonContiguous Context triple: [Overkwartier van Gelre, nonContiguous, true]
-
A.
isNonContiguous
chosen
Indicates that the related elements are separated by one or more gaps and do not form a single continuous sequence or region.
-
B.
notCoterminousWith
Indicates that two entities do not share the same boundaries in space, time, or extent and therefore are not exactly coincident.
-
C.
notCrossing
Indicates that two entities do not intersect, overlap, or pass through each other in space or along their paths.
-
D.
nonExclusive
Indicates that the relationship or access is shared among multiple parties and is not limited to a single, exclusive holder.
-
E.
nonSelective
Indicates that the relationship or action is applied without discrimination or preference among the available options or targets.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.