Triple
T8997855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Arts and Sciences Distinguished Professor |
E214963
|
entity |
| Predicate | mayBeTimeLimited |
P22110
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [College of Arts and Sciences Distinguished Professor, mayBeTimeLimited, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayBeTimeLimited Context triple: [College of Arts and Sciences Distinguished Professor, mayBeTimeLimited, yes]
-
A.
timeLimited
chosen
Indicates that the relationship or action is constrained to occur or remain valid only within a specific, limited time period.
-
B.
mayBeCappedBy
Indicates that one entity can optionally serve as a covering or cap for another entity.
-
C.
hasLimitation
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
D.
isLimitOf
Indicates that one quantity, function, or sequence approaches a particular value as its input or index approaches some specified point or condition.
-
E.
hasTypicalUseTime
Indicates the usual or expected duration or time period during which something is commonly used or in operation.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc68e0d3588190bdab0e2b86b09228 |
completed | April 1, 2026, 12:37 a.m. |
| PD | Predicate disambiguation | batch_69cc5edd6cb48190b4fc6d6ca0418056 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:05 p.m.