Triple
T33096135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adjunct professor at University of Waterloo |
E846912
|
entity |
| Predicate | mayNotInclude |
P175800
|
FINISHED |
| Object | eligibility for tenure |
—
|
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: eligibility for tenure | Statement: [Adjunct professor at University of Waterloo, mayNotInclude, eligibility for tenure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayNotInclude Context triple: [Adjunct professor at University of Waterloo, mayNotInclude, eligibility for tenure]
-
A.
mayAlsoInclude
Indicates that something can optionally contain or encompass additional elements beyond those primarily specified.
-
B.
mayNot
Indicates that an entity is not permitted or is prohibited from performing a particular action or entering into a specified relationship.
-
C.
mayIncludeMode
Indicates that one entity is allowed to contain or support a particular mode as one of its possible configurations or options.
-
D.
mayNotReduce
Indicates that one entity is prohibited from decreasing, diminishing, or lowering some quantity, quality, or resource associated with another entity.
-
E.
mayIncludeFeature
Indicates that one entity is allowed or able to contain, incorporate, or be associated with a particular feature.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d6a482fc8190b526291cd99b8696 |
completed | May 3, 2026, 5:01 a.m. |
Created at: May 1, 2026, 1:26 a.m.