Triple
T10593316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Board of Overseers of Harvard University |
E250045
|
entity |
| Predicate | hasTermStructure |
P94820
|
FINISHED |
| Object | fixed terms for members |
—
|
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: fixed terms for members | Statement: [Board of Overseers of Harvard University, hasTermStructure, fixed terms for members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTermStructure Context triple: [Board of Overseers of Harvard University, hasTermStructure, fixed terms for members]
-
A.
termStructure
Indicates a hierarchical or compositional organization of terms, showing how smaller term units are structurally related to form larger expressions.
-
B.
hasStructureType
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
C.
hasAcademicTermStructure
Indicates that an entity is organized according to a specific pattern or system of academic terms (such as semesters, quarters, or trimesters).
-
D.
interestRateStructure
Indicates the relationship defining how interest rates are organized, structured, or vary (e.g., over time, by term, or by conditions) within a financial arrangement.
-
E.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5277da8048190add007ca0c37253e |
completed | April 7, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:40 p.m.