Triple
T10791115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chartres Cathedral |
E254579
|
entity |
| Predicate | heightOfNorthTower |
P18664
|
FINISHED |
| Object | 115 m |
—
|
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: 115 m | Statement: [Chartres Cathedral, heightOfNorthTower, 115 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heightOfNorthTower Context triple: [Chartres Cathedral, heightOfNorthTower, 115 m]
-
A.
approximateHeightOfTallestStructure
Indicates the estimated height value associated with the tallest structure in a given context or set.
-
B.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
C.
storeysOfTallestTower
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
D.
hasTowerHeight
chosen
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
-
E.
buildingHeightContext
Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732f6dfcc81909096895c588ef46f |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.