Triple
T28842887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannons |
E728368
|
entity |
| Predicate | influencedBuilding |
P57645
|
FINISHED |
| Object | Middlesex Hospital (via reused materials) |
—
|
NE NERFINISHED |
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: Middlesex Hospital (via reused materials) | Statement: [Cannons, influencedBuilding, Middlesex Hospital (via reused materials)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedBuilding Context triple: [Cannons, influencedBuilding, Middlesex Hospital (via reused materials)]
-
A.
buildingInspired
Indicates that one building’s design, style, or concept was influenced or derived from another building.
-
B.
architecturalInfluence
Indicates that one architectural style, structure, or designer has had a formative impact on the design, style, or features of another.
-
C.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
D.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
E.
notableBuildingAssociated
chosen
Indicates a relationship where a notable or significant building is associated with, connected to, or relevant to a given entity.
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 28, 2026, 6:41 a.m.