Triple
T28194593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Microbiology and Immunology |
E716408
|
entity |
| Predicate | typicalLocationWithin |
P40
|
FINISHED |
| Object | faculty of medicine |
—
|
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: faculty of medicine | Statement: [Department of Microbiology and Immunology, typicalLocationWithin, faculty of medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLocationWithin Context triple: [Department of Microbiology and Immunology, typicalLocationWithin, faculty of medicine]
-
A.
likelyLocatedIn
Indicates that an entity is probably situated within or associated with a particular location, though not with absolute certainty.
-
B.
typicalUseLocation
Indicates the usual or most common location where an entity is used or operates.
-
C.
oftenLocatedAt
Indicates that an entity is frequently or commonly found at, or associated with being in, a particular location.
-
D.
locatedWith
Indicates that two or more entities are situated together in the same place or spatial context.
-
E.
locatedIn
chosen
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a0075be7f54819081ab12bc1dab53bb |
completed | May 10, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_6a0073a19030819098c23faa3adcb96e |
completed | May 10, 2026, 12:01 p.m. |
Created at: April 27, 2026, 10:27 p.m.