Triple
T533224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The National Archives, Kew |
E12269
|
entity |
| Predicate | hasBuildingFeature |
P6684
|
FINISHED |
| Object | purpose-built archival repository |
—
|
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: purpose-built archival repository | Statement: [The National Archives, Kew, hasBuildingFeature, purpose-built archival repository]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingFeature Context triple: [The National Archives, Kew, hasBuildingFeature, purpose-built archival repository]
-
A.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
B.
hasArchitecturalFeature
chosen
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
C.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
D.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
-
E.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b3e49081909810fa417b31306f |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.