Triple
T26201036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babar Azam |
E655229
|
entity |
| Predicate | formerFranchise |
P181200
|
FINISHED |
| Object | Karachi Kings |
—
|
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 Kings | Statement: [Babar Azam, formerFranchise, Karachi Kings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerFranchise Context triple: [Babar Azam, formerFranchise, Karachi Kings]
-
A.
previousFranchiseName
Indicates that an entity previously operated under a different franchise name, specifying what that earlier franchise name was.
-
B.
predecessorFranchise
Indicates that one franchise directly precedes and is succeeded by another franchise in a series or lineage.
-
C.
franchiseLegacy
Indicates that an entity continues, inherits, or extends the storyline, brand, or creative universe established by an earlier work in the same franchise.
-
D.
previousFranchiseCity
Indicates that a city was formerly the home location of a particular franchise before it moved or relocated.
-
E.
originalFranchiseOf
Indicates that one entity is the source or originating franchise from which another franchise, adaptation, or derivative work is based or derived.
- F. None of above. chosen
Provenance (4 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f76759b3c48190ad8f1b33596f98c4 |
completed | May 3, 2026, 3:18 p.m. |
Created at: April 26, 2026, 8:48 p.m.