Triple
T11431800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanded Lok Sabha constituency |
E270901
|
entity |
| Predicate | formerAssemblySegment |
P63908
|
FINISHED |
| Object |
Loha
Loha is a town and former Maharashtra Legislative Assembly constituency in the Nanded district of the Indian state of Maharashtra.
|
E924983
|
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: Loha | Statement: [Nanded Lok Sabha constituency, formerAssemblySegment, Loha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loha Context triple: [Nanded Lok Sabha constituency, formerAssemblySegment, Loha]
-
A.
Loha
Loha is a 1987 Indian Hindi-language action film featuring Persis Khambatta in a prominent role.
-
B.
Ratna
Ratna is an Indonesian-born dancer and model who became known internationally as the second wife of French photographer Henri Cartier-Bresson.
-
C.
Aokaparangi
Aokaparangi is a mountain peak in New Zealand’s Tararua Range, popular with trampers for its alpine terrain and expansive views.
-
D.
Rohilla
The Rohilla are a Pashtun-origin community historically known for establishing the Rohilkhand region in northern India and playing a significant role in 18th-century North Indian politics.
-
E.
Kahaku
Kahaku is Japan’s National Museum of Nature and Science in Tokyo, renowned for its extensive natural history and scientific collections and exhibitions.
- 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: Loha Triple: [Nanded Lok Sabha constituency, formerAssemblySegment, Loha]
Generated description
Loha is a town and former Maharashtra Legislative Assembly constituency in the Nanded district of the Indian state of Maharashtra.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Loha Target entity description: Loha is a town and former Maharashtra Legislative Assembly constituency in the Nanded district of the Indian state of Maharashtra.
-
A.
Loha
Loha is a 1987 Indian Hindi-language action film featuring Persis Khambatta in a prominent role.
-
B.
Ratna
Ratna is an Indonesian-born dancer and model who became known internationally as the second wife of French photographer Henri Cartier-Bresson.
-
C.
Aokaparangi
Aokaparangi is a mountain peak in New Zealand’s Tararua Range, popular with trampers for its alpine terrain and expansive views.
-
D.
Rohilla
The Rohilla are a Pashtun-origin community historically known for establishing the Rohilkhand region in northern India and playing a significant role in 18th-century North Indian politics.
-
E.
Kahaku
Kahaku is Japan’s National Museum of Nature and Science in Tokyo, renowned for its extensive natural history and scientific collections and exhibitions.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d808855a7481909314f90ad92aae68 |
completed | April 9, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b8e212088190b611333d5de05757 |
completed | April 20, 2026, 5:25 a.m. |
| NEDg | Description generation | batch_69e5c28f24108190aa48ca90440d6d7f |
completed | April 20, 2026, 6:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c474d2c88190882a55ae6621daef |
completed | April 20, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:35 p.m.