Triple
T18790354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lille town hall |
E459495
|
entity |
| Predicate | hasBelfryHeight |
P18664
|
FINISHED |
| Object | approximately 104 meters |
—
|
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: approximately 104 meters | Statement: [Lille town hall, hasBelfryHeight, approximately 104 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBelfryHeight Context triple: [Lille town hall, hasBelfryHeight, approximately 104 meters]
-
A.
hasTowerHeight
chosen
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
-
B.
hasBellTower
Indicates that one entity (typically a building or structure) possesses or includes a bell tower as part of it.
-
C.
belfryListedAs
Indicates that a belfry is officially recorded or registered under a particular listing or designation.
-
D.
hasBellTowerHeightSignificance
Indicates that the height of a bell tower holds particular importance or relevance in a given context or relationship.
-
E.
hasBellTowerLocation
Indicates the specific location where a bell tower is situated or attached relative to another structure or place.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5978599008190aaceaff1b1e0a2c7 |
completed | April 20, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.