Triple
T3796950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government College, Lahore |
E91592
|
entity |
| Predicate | alumniField |
P48900
|
FINISHED |
| Object | politics |
—
|
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: politics | Statement: [Government College, Lahore, alumniField, politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alumniField Context triple: [Government College, Lahore, alumniField, politics]
-
A.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
B.
alumniOfProgram
Indicates that a person previously completed or participated in a specific educational or training program.
-
C.
educationField
chosen
Indicates the academic or professional discipline in which an entity has been educated or trained.
-
D.
hasAlumniNetwork
Indicates that an entity maintains or is associated with an organized network or community of its former members or graduates.
-
E.
hadAlumniRole
Indicates that an entity previously held a role or position as an alumnus/alumna of another entity (such as an 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69aee743c8d08190a9f9c97b836bd703 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.