Triple
T8147648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATK Mohun Bagan FC |
E190253
|
entity |
| Predicate | hasRivalClubCity |
P46046
|
FINISHED |
| Object | Kolkata-based clubs |
—
|
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: Kolkata-based clubs | Statement: [ATK Mohun Bagan FC, hasRivalClubCity, Kolkata-based clubs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRivalClubCity Context triple: [ATK Mohun Bagan FC, hasRivalClubCity, Kolkata-based clubs]
-
A.
hasLocalRivalry
Indicates that there is an ongoing competitive or adversarial relationship between entities that are geographically close or share the same local area.
-
B.
hasForeignRival
Indicates that an entity has at least one rival that is based in or originates from a different country or foreign jurisdiction.
-
C.
rivalryInvolvesCity
chosen
Indicates that a rivalry relationship includes or is associated with a particular city as one of its involved locations.
-
D.
hasHomeStadiumInRivalry
Indicates that one entity’s home stadium is the venue used when it participates in a rivalry with another entity.
-
E.
hasFranchiseFromCity
Indicates that an entity holds a franchise or licensed operation originating from, or granted by, a particular city.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb447d6b1881908ff3fa25af6b4e80 |
completed | March 31, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:36 p.m.