Triple
T19281296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Datia Palace |
E482192
|
entity |
| Predicate | hasView |
P854
|
FINISHED |
| Object |
Datia town
Datia town is a historic urban center in Madhya Pradesh, India, known for its hilltop palaces, temples, and rich Bundelkhand architectural heritage.
|
E1367271
|
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: Datia town | Statement: [Datia Palace, hasView, Datia town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Datia town Context triple: [Datia Palace, hasView, Datia town]
-
A.
Sohna town
Sohna town is a rapidly developing suburban area in Haryana, India, known for its hot springs, proximity to the Aravalli hills, and growing residential and commercial hubs.
-
B.
Amalner
Amalner is a town in the Indian state of Maharashtra known for its textile industry and as the birthplace of the Wipro company.
-
C.
Somnath town
Somnath town is a coastal pilgrimage destination in Gujarat, India, best known for the revered Somnath Temple and its scenic Arabian Sea shoreline.
-
D.
Betul city
Betul city is an urban center in the Betul district of Madhya Pradesh, India, known as a regional hub for trade, agriculture, and transportation.
-
E.
Kawardha
Kawardha is a regional dialect of the Chhattisgarhi language spoken in parts of the Indian state of Chhattisgarh.
- 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: Datia town Triple: [Datia Palace, hasView, Datia town]
Generated description
Datia town is a historic urban center in Madhya Pradesh, India, known for its hilltop palaces, temples, and rich Bundelkhand architectural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Datia town Target entity description: Datia town is a historic urban center in Madhya Pradesh, India, known for its hilltop palaces, temples, and rich Bundelkhand architectural heritage.
-
A.
Sohna town
Sohna town is a rapidly developing suburban area in Haryana, India, known for its hot springs, proximity to the Aravalli hills, and growing residential and commercial hubs.
-
B.
Amalner
Amalner is a town in the Indian state of Maharashtra known for its textile industry and as the birthplace of the Wipro company.
-
C.
Somnath town
Somnath town is a coastal pilgrimage destination in Gujarat, India, best known for the revered Somnath Temple and its scenic Arabian Sea shoreline.
-
D.
Betul city
Betul city is an urban center in the Betul district of Madhya Pradesh, India, known as a regional hub for trade, agriculture, and transportation.
-
E.
Kawardha
Kawardha is a regional dialect of the Chhattisgarhi language spoken in parts of the Indian state of Chhattisgarh.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbff1e6c819094ae6a5ad40adb65 |
completed | April 20, 2026, 10:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a070e7ba04481908e8b707d34028e58 |
completed | May 15, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_6a070f74709481909b4eb1c073db2134 |
completed | May 15, 2026, 12:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a070fccff7c819083fe388dda8e4e5a |
completed | May 15, 2026, 12:21 p.m. |
Created at: April 10, 2026, 1:30 p.m.