Triple
T81080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westminster Abbey |
E1627
|
entity |
| Predicate | towerHeight |
P1730
|
FINISHED |
| Object | approximately 69 metres |
—
|
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 69 metres | Statement: [Westminster Abbey, towerHeight, approximately 69 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: towerHeight Context triple: [Westminster Abbey, towerHeight, approximately 69 metres]
-
A.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
B.
roofHeight
Indicates the vertical distance or elevation of a roof relative to a reference level or structure.
-
C.
antennaSpireHeight
chosen
Indicates the vertical measurement of an object's antenna or spire from its base to its highest point.
-
D.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
E.
statueHeight
Indicates the height measurement of a statue in some specified unit.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.