Triple
T37698537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pakistan Civil Aviation Authority Schools and Colleges |
E938991
|
entity |
| Predicate | hasCampusInCity |
P54224
|
FINISHED |
| Object | Karachi |
—
|
NE NERFINISHED |
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: Karachi | Statement: [Pakistan Civil Aviation Authority Schools and Colleges, hasCampusInCity, Karachi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusInCity Context triple: [Pakistan Civil Aviation Authority Schools and Colleges, hasCampusInCity, Karachi]
-
A.
hasCampusCity
chosen
Indicates that an educational institution or campus is located in a particular city.
-
B.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
C.
containsUniversityCity
Indicates that a given region or area includes within its boundaries a city that hosts a university.
-
D.
hasMainCampus
Indicates that an educational institution is primarily based at or chiefly associated with a particular campus location.
-
E.
hasFlagshipCampusOf
Indicates that one location serves as the primary or main campus for a particular institution or organization.
- 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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a002dd4066c8190945a09ed82f44f3f |
completed | May 10, 2026, 7:03 a.m. |
| PD | Predicate disambiguation | batch_6a002b141f4081909999e14988105f3a |
completed | May 10, 2026, 6:52 a.m. |
Created at: May 3, 2026, 4:18 p.m.