Triple
T14490216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shimla Hills |
E359340
|
entity |
| Predicate | hasHillStation |
P24292
|
FINISHED |
| Object |
Naldehra
Naldehra is a serene hill station in the Indian state of Himachal Pradesh, known for its lush cedar forests, scenic mountain views, and historic golf course.
|
E1103595
|
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: Naldehra | Statement: [Shimla Hills, hasHillStation, Naldehra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naldehra Context triple: [Shimla Hills, hasHillStation, Naldehra]
-
A.
Bodelva
Bodelva is a small settlement in Cornwall, England, best known as the site of the Eden Project’s iconic biomes and visitor attraction.
-
B.
Vallirana
Vallirana is a municipality in the Baix Llobregat comarca of Catalonia, Spain, located near Barcelona and known for its surrounding natural landscapes and caves.
-
C.
Novilara
Novilara is an archaeological site and locality in the Marche region of Italy, known for its ancient Picene culture remains and notable funerary stelae.
-
D.
Lohra
Lohra is a small municipality in the Marburg-Biedenkopf district of the German state of Hesse.
-
E.
Arnalta
Arnalta is a comic nurse character in Claudio Monteverdi’s opera "L'incoronazione di Poppea," known for her earthy wisdom and humorous commentary.
- 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: Naldehra Triple: [Shimla Hills, hasHillStation, Naldehra]
Generated description
Naldehra is a serene hill station in the Indian state of Himachal Pradesh, known for its lush cedar forests, scenic mountain views, and historic golf course.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naldehra Target entity description: Naldehra is a serene hill station in the Indian state of Himachal Pradesh, known for its lush cedar forests, scenic mountain views, and historic golf course.
-
A.
Bodelva
Bodelva is a small settlement in Cornwall, England, best known as the site of the Eden Project’s iconic biomes and visitor attraction.
-
B.
Vallirana
Vallirana is a municipality in the Baix Llobregat comarca of Catalonia, Spain, located near Barcelona and known for its surrounding natural landscapes and caves.
-
C.
Novilara
Novilara is an archaeological site and locality in the Marche region of Italy, known for its ancient Picene culture remains and notable funerary stelae.
-
D.
Lohra
Lohra is a small municipality in the Marburg-Biedenkopf district of the German state of Hesse.
-
E.
Arnalta
Arnalta is a comic nurse character in Claudio Monteverdi’s opera "L'incoronazione di Poppea," known for her earthy wisdom and humorous commentary.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930d820481908b9813014dd02540 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9334708190baa2f8094df3c09e |
completed | May 8, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69fd6f80e3a081908c43915275898852 |
completed | May 8, 2026, 5:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7016a3c48190a1ea2fefeea92c60 |
completed | May 8, 2026, 5:09 a.m. |
Created at: April 10, 2026, 1:20 a.m.