Triple
T12606328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pakistan Military Academy |
E300986
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kakul |
E300986
|
NE 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: Kakul | Statement: [Pakistan Military Academy, locatedIn, Kakul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kakul Context triple: [Pakistan Military Academy, locatedIn, Kakul]
-
A.
Kakul
chosen
Kakul is a village near Abbottabad in Pakistan, best known for hosting the Pakistan Military Academy, the country’s premier officer training institution.
-
B.
Kakarla
Kakarla is an Indian surname notably associated with the renowned Carnatic composer Tyagaraja (Kakarla Tyagabrahmam).
-
C.
Kala
Kala is the critically acclaimed 2007 studio album by British-Sri Lankan artist M.I.A., known for its eclectic global influences and politically charged themes.
-
D.
Kala
Kala is a character from the Old Javanese epic poem Kakawin Sutasoma, often associated with destructive or fearsome aspects within the narrative’s moral and spiritual themes.
-
E.
Kaala
Kaala is a 2018 Indian Tamil-language action drama film starring Rajinikanth as a slum leader fighting for the rights of oppressed people in Mumbai.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e7f2dc8190a42cab7a0e5ea7f3 |
completed | April 10, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ecd1b748190bd961497b30e1ae5 |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:11 p.m.