Triple
T25825854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bharat Bhavan |
E650526
|
entity |
| Predicate | hasTheatreSpace |
P17368
|
FINISHED |
| Object |
Natyagriha
Natyagriha is a prominent theatre auditorium within the Bharat Bhavan arts complex in Bhopal, known for hosting a wide range of cultural and performing arts events.
|
E1697045
|
NE FINISHED |
How this triple was built (3 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: Natyagriha | Statement: [Bharat Bhavan, hasTheatreSpace, Natyagriha]
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: Natyagriha Triple: [Bharat Bhavan, hasTheatreSpace, Natyagriha]
Generated description
Natyagriha is a prominent theatre auditorium within the Bharat Bhavan arts complex in Bhopal, known for hosting a wide range of cultural and performing arts events.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTheatreSpace Context triple: [Bharat Bhavan, hasTheatreSpace, Natyagriha]
-
A.
isPartOfTheater
Indicates that one entity functions as a component, section, or subdivision within a larger theater (such as a theater building, complex, or organizational unit).
-
B.
hasAuditorium
chosen
Indicates that one entity possesses or includes an auditorium as part of its facilities.
-
C.
hasTheatreDistrictRole
Indicates that an entity holds a specific role, function, or designation within a theatre district.
-
D.
isIndoorTheatre
Indicates that a theatre is located indoors rather than outdoors.
-
E.
theaterSupport
Indicates that one entity provides assistance, resources, or services to support another entity in the context of theater or theatrical activities.
- F. None of above.
Provenance (6 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6019443b48190bb7e5da78c18d3cf |
completed | May 2, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10da2807ec81908e6bdff8926813ae |
completed | May 22, 2026, 10:35 p.m. |
| NEDg | Description generation | batch_6a10dd8a06b881909f8a9ca5d7d77576 |
completed | May 22, 2026, 10:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10de47e1f0819082aae48923ded2c1 |
completed | May 22, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f5afec3e94819080d9ba86cf8c866e |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 22, 2026, 7:36 a.m.