Triple
T31341127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omloop Het Nieuwsblad |
E799307
|
entity |
| Predicate | hasSectorType |
P198697
|
FINISHED |
| Object | cobbled sectors |
—
|
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: cobbled sectors | Statement: [Omloop Het Nieuwsblad, hasSectorType, cobbled sectors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectorType Context triple: [Omloop Het Nieuwsblad, hasSectorType, cobbled sectors]
-
A.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
-
B.
hasMarketSector
Indicates that an entity operates within, is associated with, or belongs to a particular market sector or industry segment.
-
C.
hasSectorization
Indicates that one entity is divided into, assigned to, or associated with specific sectors defined by another entity.
-
D.
hasOccupationSector
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
E.
hasSectorClassificationStandard
Indicates that an entity is associated with a particular sector classification standard used to categorize its industry or economic activity.
- 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_69f224e3f6ac8190a13488516abca7c9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
| PDg | Predicate description generation | batch_69feff703fec8190ab7d0633e0cc5459 |
completed | May 9, 2026, 9:33 a.m. |
Created at: April 29, 2026, 9:16 p.m.