Triple
T922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim the Beaver |
E18
|
entity |
| Predicate | campus |
P269
|
FINISHED |
| Object | MIT campus in Cambridge, Massachusetts |
—
|
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: MIT campus in Cambridge, Massachusetts | Statement: [Tim the Beaver, campus, MIT campus in Cambridge, Massachusetts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campus Context triple: [Tim the Beaver, campus, MIT campus in Cambridge, Massachusetts]
-
A.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
B.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
C.
hasMainCampus
Indicates that an educational institution is primarily based at or chiefly associated with a particular campus location.
-
D.
hasAdditionalCampus
Indicates that an educational institution maintains one or more campuses in addition to its primary or main campus.
-
E.
academicStructure
Indicates a hierarchical or organizational relationship within an academic system, such as how programs, departments, courses, or degrees are structured and related to one another.
- 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23211f05c8190b8deb03a8540d84d |
completed | Feb. 28, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69a230c2c48481908beb1db3cc9768aa |
completed | Feb. 28, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69a23211181c81909c2db8796d2aded4 |
completed | Feb. 28, 2026, 12:08 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.