Triple
T3056883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington College |
E60501
|
entity |
| Predicate | hasWritingProgram |
P2489
|
FINISHED |
| Object | strong emphasis on writing |
—
|
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: strong emphasis on writing | Statement: [Washington College, hasWritingProgram, strong emphasis on writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingProgram Context triple: [Washington College, hasWritingProgram, strong emphasis on writing]
-
A.
hasEducationalProgram
chosen
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
hasProgramme
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
-
C.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
-
D.
madeProgram
Indicates that one entity created, developed, or authored a program (such as software or a coded application).
-
E.
hasArtProgram
Indicates that an entity offers or participates in an art-related educational or creative program.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e13f16c81909e11ed1444c71151 |
completed | March 8, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.