Triple
T381546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JJ Thomson Avenue, Cambridge |
E8689
|
entity |
| Predicate | hasPrimaryUser |
P2090
|
FINISHED |
| Object | university staff |
—
|
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: university staff | Statement: [JJ Thomson Avenue, Cambridge, hasPrimaryUser, university staff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryUser Context triple: [JJ Thomson Avenue, Cambridge, hasPrimaryUser, university staff]
-
A.
hasUser
Indicates that an entity is associated with or linked to a specific user.
-
B.
primaryUser
chosen
Indicates that the referenced user is the main or principal user associated with a given account, resource, or context.
-
C.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related service.
-
D.
hasPrimaryMeeting
Indicates that an entity is associated with its main or most important meeting, distinguishing it from other meetings it may have.
-
E.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2e3d5c8190b358bd9fd6b16a14 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96602188190b0cbc167f55a9237 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.