Triple
T7450130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nainital |
E171986
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Tiffin Top
Tiffin Top is a popular hilltop viewpoint near Nainital, Uttarakhand, known for its panoramic views of the surrounding mountains and the town below.
|
E665065
|
NE FINISHED |
How this triple was built (4 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: Tiffin Top | Statement: [Nainital, hasAttraction, Tiffin Top]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiffin Top Context triple: [Nainital, hasAttraction, Tiffin Top]
-
A.
Topshe
Topshe is the young cousin and loyal assistant of detective Feluda in Satyajit Ray’s popular Bengali mystery stories.
-
B.
Tupper
Tupper is a surname of English and Scottish origin borne by various notable individuals across fields such as politics, literature, and the arts.
-
C.
Tisch
Tisch is a surname most prominently associated with the American Tisch family, known for their influence in business, philanthropy, and the entertainment industry.
-
D.
Mantel
Mantel is a surname most prominently associated with the acclaimed British novelist Hilary Mantel, known for her historical fiction.
-
E.
Brick Top
Brick Top is a ruthless and sadistic London crime boss in the film "Snatch," known for his brutal methods and memorable, darkly comic dialogue.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tiffin Top Triple: [Nainital, hasAttraction, Tiffin Top]
Generated description
Tiffin Top is a popular hilltop viewpoint near Nainital, Uttarakhand, known for its panoramic views of the surrounding mountains and the town below.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tiffin Top Target entity description: Tiffin Top is a popular hilltop viewpoint near Nainital, Uttarakhand, known for its panoramic views of the surrounding mountains and the town below.
-
A.
Topshe
Topshe is the young cousin and loyal assistant of detective Feluda in Satyajit Ray’s popular Bengali mystery stories.
-
B.
Tupper
Tupper is a surname of English and Scottish origin borne by various notable individuals across fields such as politics, literature, and the arts.
-
C.
Tisch
Tisch is a surname most prominently associated with the American Tisch family, known for their influence in business, philanthropy, and the entertainment industry.
-
D.
Mantel
Mantel is a surname most prominently associated with the acclaimed British novelist Hilary Mantel, known for her historical fiction.
-
E.
Brick Top
Brick Top is a ruthless and sadistic London crime boss in the film "Snatch," known for his brutal methods and memorable, darkly comic dialogue.
- F. None of above. chosen
Provenance (5 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f38af3fc8190bc5c57ca89d976bc |
completed | March 27, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c827b54a4881909f800bf37990a297 |
completed | March 28, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69c828ca24bc81909357b9f40a9004af |
completed | March 28, 2026, 7:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8297c1de4819099acfac611a519e5 |
completed | March 28, 2026, 7:18 p.m. |
Created at: March 27, 2026, 3:14 p.m.