Triple
T20221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tozzer Library |
E401
|
entity |
| Predicate | buildingType |
P1844
|
FINISHED |
| Object | library building |
—
|
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: library building | Statement: [Tozzer Library, buildingType, library building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingType Context triple: [Tozzer Library, buildingType, library building]
-
A.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
-
B.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
C.
usesBuilding
Indicates that one entity makes use of, occupies, or operates within a particular building.
-
D.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
E.
architecturalStyle
Indicates the architectural design tradition, movement, or style that characterizes the form and appearance of a structure or built work.
- F. None of above. chosen
Provenance (4 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a24702d4988190a54a4e578b7c919e |
completed | Feb. 28, 2026, 1:38 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.