Triple
T16712306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Newport University |
E406137
|
entity |
| Predicate | offersHonorsPrograms |
P124319
|
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: [Christopher Newport University, offersHonorsPrograms, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersHonorsPrograms Context triple: [Christopher Newport University, offersHonorsPrograms, true]
-
A.
offersFellowshipPrograms
Indicates that an entity provides or makes available fellowship programs to individuals or other entities.
-
B.
offersProgramLevel
Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
-
C.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
D.
offersInternationalPrograms
Indicates that an institution or organization provides programs or courses available to participants from other countries or across national borders.
-
E.
offersProfessionalPrograms
Indicates that an entity provides formal, career-oriented educational or training programs to others.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e386530d9c8190b91ec3aac7dc2518 |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:20 a.m.