Triple
T141611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayden Library |
E2862
|
entity |
| Predicate | hasTypeOfSpace |
P2836
|
FINISHED |
| Object | quiet study areas |
—
|
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: quiet study areas | Statement: [Hayden Library, hasTypeOfSpace, quiet study areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfSpace Context triple: [Hayden Library, hasTypeOfSpace, quiet study areas]
-
A.
hasSpacetimeRegion
Indicates that something occupies, is associated with, or is bounded by a specific region in spacetime.
-
B.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
C.
hasTypeOfResource
Indicates that an entity is associated with a specific category or kind of resource it represents or utilizes.
-
D.
hasCapacityType
Indicates that an entity possesses a specific kind or classification of capacity or capability.
-
E.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.