Triple
T33734699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law Library (University at Buffalo) |
E864379
|
entity |
| Predicate | hasMaterialFormat |
P1845
|
FINISHED |
| Object | print resources |
—
|
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: print resources | Statement: [Law Library (University at Buffalo), hasMaterialFormat, print resources]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaterialFormat Context triple: [Law Library (University at Buffalo), hasMaterialFormat, print resources]
-
A.
hasMaterialFormOnSet
Indicates that something possesses a tangible, physical form or embodiment during the production or staging of a set.
-
B.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
C.
hasFileFormat
Indicates that one entity (typically a digital file or resource) is encoded, stored, or represented using a specific file format defined by the other entity.
-
D.
hasWorkingFormat
Indicates that one entity possesses or is associated with a functional or operational format of another entity.
-
E.
hasProductionFormat
Indicates that an entity is associated with, or presented in, a particular production or media format.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01378bf05c8190af9f5e06a2810c7d |
completed | May 11, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_6a0137277c6c8190bcec341f2a0757c4 |
completed | May 11, 2026, 1:55 a.m. |
Created at: May 1, 2026, 1:44 a.m.