Triple
T4803195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WXYC |
E106883
|
entity |
| Predicate | campusRadio |
P60219
|
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: [WXYC, campusRadio, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusRadio Context triple: [WXYC, campusRadio, true]
-
A.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
B.
campusUse
Indicates that something is intended for, associated with, or occurring in the use or activities of a campus or campus community.
-
C.
campusCluster
Indicates a relationship where multiple campus locations or facilities are grouped or associated together as part of the same cluster or complex.
-
D.
campusLife
Indicates the overall experience, activities, and social environment associated with being part of a particular campus or educational institution.
-
E.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another 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_69bd43f6a1e08190bf0a372bfc336ee5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1c43a48190a65e56b1624a2339 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6ff731188190a9903602122d4ff9 |
completed | March 20, 2026, 4:04 p.m. |
Created at: March 20, 2026, 1:23 p.m.