Triple
T3197618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bharatanatyam |
E66970
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
tillana
Tillana is a lively, rhythm-focused concluding piece in Indian classical dance and music, especially prominent in Bharatanatyam performances.
|
E336761
|
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: tillana | Statement: [Bharatanatyam, hasComponent, tillana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tillana Context triple: [Bharatanatyam, hasComponent, tillana]
-
A.
Tonalá
Tonalá is a municipality and city in the Guadalajara metropolitan area of Jalisco, Mexico, known for its traditional pottery and handicrafts.
-
B.
Tulunan
Tulunan is a rural municipality in the province of North Cotabato on the island of Mindanao in the Philippines, known primarily for its agricultural economy.
-
C.
Tullistes
Tullistes are the inhabitants of the French city of Tulle, located in the Corrèze department in central France.
-
D.
Tinajo
Tinajo is a rural municipality on the western side of Lanzarote in Spain’s Canary Islands, known for its volcanic landscapes and proximity to Timanfaya National Park.
-
E.
Tilakkam
Tilakkam is a small island that forms part of the Kalpeni atoll in the Lakshadweep archipelago of India.
- 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: tillana Triple: [Bharatanatyam, hasComponent, tillana]
Generated description
Tillana is a lively, rhythm-focused concluding piece in Indian classical dance and music, especially prominent in Bharatanatyam performances.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: tillana Target entity description: Tillana is a lively, rhythm-focused concluding piece in Indian classical dance and music, especially prominent in Bharatanatyam performances.
-
A.
Tonalá
Tonalá is a municipality and city in the Guadalajara metropolitan area of Jalisco, Mexico, known for its traditional pottery and handicrafts.
-
B.
Tulunan
Tulunan is a rural municipality in the province of North Cotabato on the island of Mindanao in the Philippines, known primarily for its agricultural economy.
-
C.
Tullistes
Tullistes are the inhabitants of the French city of Tulle, located in the Corrèze department in central France.
-
D.
Tinajo
Tinajo is a rural municipality on the western side of Lanzarote in Spain’s Canary Islands, known for its volcanic landscapes and proximity to Timanfaya National Park.
-
E.
Tilakkam
Tilakkam is a small island that forms part of the Kalpeni atoll in the Lakshadweep archipelago of India.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada7192994819084817307065a25e2 |
completed | March 8, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bb7cd488190ae95c140d9cda296 |
completed | March 12, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69b24d39e77c8190818f71a3298852d7 |
completed | March 12, 2026, 5:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b25178f3c08190be78bdbd0cdfc5f3 |
completed | March 12, 2026, 5:39 a.m. |
Created at: March 8, 2026, 3:07 p.m.