Triple
T14801436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | موتی مسجد (لال قلعہ، دہلی) |
E347918
|
entity |
| Predicate | سیاحتی درجہ |
P5644
|
FINISHED |
| Object | سیاحوں کے لیے اہم کشش |
—
|
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: سیاحوں کے لیے اہم کشش | Statement: [موتی مسجد (لال قلعہ، دہلی), سیاحتی درجہ, سیاحوں کے لیے اہم کشش]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: سیاحتی درجہ Context triple: [موتی مسجد (لال قلعہ، دہلی), سیاحتی درجہ, سیاحوں کے لیے اہم کشش]
-
A.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
B.
hasTourismRating
Indicates that an entity has been assigned a specific tourism-related quality or rating, reflecting its appeal or suitability for tourists.
-
C.
resort
Indicates that one entity is used or turned to as a final or alternative option by another entity, often after other possibilities have been exhausted.
-
D.
hasTouristRank
Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
-
E.
isMajorAttractionFor
chosen
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd62c36c81909c2993dc7d1a79ea |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.