Triple
T4585140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sialkot |
E101948
|
entity |
| Predicate | sportsGoodsShare |
P58141
|
FINISHED |
| Object | major share of world hand-stitched footballs |
—
|
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: major share of world hand-stitched footballs | Statement: [Sialkot, sportsGoodsShare, major share of world hand-stitched footballs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsGoodsShare Context triple: [Sialkot, sportsGoodsShare, major share of world hand-stitched footballs]
-
A.
sportsBrand
Indicates that one entity is a sports-related brand or label associated with the other entity.
-
B.
sportsSponsored
Indicates that one entity provides financial or material sponsorship to support another entity’s sports-related activities or events.
-
C.
sponsorSport
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
-
D.
sportOwned
Indicates that one entity possesses ownership or control over a particular sport.
-
E.
sportsName
Indicates the specific sport associated with or played in a given context or event.
- 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_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59056bb48190ba1e0b5beda9bdc4 |
completed | March 20, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69bd522acbcc8190bf24d9517793a2c1 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:10 p.m.