Triple
T353780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swarthmore College |
E7499
|
entity |
| Predicate | undergraduateOnly |
P12171
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Swarthmore College, undergraduateOnly, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: undergraduateOnly Context triple: [Swarthmore College, undergraduateOnly, true]
-
A.
undergraduatesApprox
Indicates that the relationship involves an approximate or estimated number of undergraduate students associated with an entity.
-
B.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
C.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
D.
college
Indicates that an entity is a college-level educational institution attended by or associated with another entity.
-
E.
university
Indicates that an educational institution of higher learning is associated with or attended by a given entity.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb80f524819093f4c2c18c3d615f |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e9571bd88190b6fcb16f21604720 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0a4c448190a8a179daa9b90645 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.