Triple
T12741832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fazilka |
E304505
|
entity |
| Predicate | belongsToCulturalZone |
P74006
|
FINISHED |
| Object | Punjabi culture |
—
|
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: Punjabi culture | Statement: [Fazilka, belongsToCulturalZone, Punjabi culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToCulturalZone Context triple: [Fazilka, belongsToCulturalZone, Punjabi culture]
-
A.
culturalAreaIncludes
Indicates that a broader cultural area encompasses or contains a smaller cultural region or entity within its scope.
-
B.
belongsToUrbanZone
Indicates that something is located within, or is a part of, a designated urban zone or area.
-
C.
belongsToLinguisticRegion
Indicates that one linguistic entity (such as a language, dialect, or speech variety) is associated with or situated within a particular linguistic region or area.
-
D.
belongsToEthnographicRegion
chosen
Indicates that an entity is associated with or situated within a specific ethnographic region defined by shared cultural or ethnic characteristics.
-
E.
hasEconomicZoneType
Indicates the specific classification or category of economic zone associated with an entity.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:26 p.m.