Triple
T4812173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isis |
E107095
|
entity |
| Predicate | hasCourseDirection |
P20524
|
FINISHED |
| Object | generally east–west through Oxford |
—
|
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: generally east–west through Oxford | Statement: [Isis, hasCourseDirection, generally east–west through Oxford]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseDirection Context triple: [Isis, hasCourseDirection, generally east–west through Oxford]
-
A.
courseDirection
chosen
Indicates the orientation or path that something follows or is intended to follow, such as the direction of movement, flow, or progression.
-
B.
hasPrimaryCourse
Indicates that an entity is associated with its main or principal course in a given context (such as a meal, curriculum, or sequence of offerings).
-
C.
taughtCourse
Indicates that an entity (typically an instructor) has taught a particular course.
-
D.
hasModeOfStudy
Indicates the method or format by which an entity (typically a learner) undertakes their studies, such as full-time, part-time, online, or in-person.
-
E.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:23 p.m.