Triple
T7772309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madhabi Mukherjee |
E179100
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Uttoran
Uttoran is a Bengali film best known for featuring acclaimed actress Madhabi Mukherjee in a prominent role.
|
E687707
|
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: Uttoran | Statement: [Madhabi Mukherjee, notableWork, Uttoran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uttoran Context triple: [Madhabi Mukherjee, notableWork, Uttoran]
-
A.
Uttigen
Uttigen is a small municipality in the canton of Bern, Switzerland, situated along the Aare River between Bern and Thun.
-
B.
Gunalda
Gunalda is a small rural town in Queensland, Australia, situated inland within the Fraser Coast Region and known for its agricultural surroundings and local community facilities.
-
C.
Uttran
Uttran is a residential locality in Botkyrka Municipality within the Stockholm County area of Sweden.
-
D.
Urft
Urft is a river in western Germany that flows through the Eifel region and feeds into the Rur (Roer) River.
-
E.
Urstein
Urstein is a locality in the municipality of Puch bei Hallein in the Austrian state of Salzburg, known for hosting the Salzburg University of Applied Sciences campus.
- 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: Uttoran Triple: [Madhabi Mukherjee, notableWork, Uttoran]
Generated description
Uttoran is a Bengali film best known for featuring acclaimed actress Madhabi Mukherjee in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Uttoran Target entity description: Uttoran is a Bengali film best known for featuring acclaimed actress Madhabi Mukherjee in a prominent role.
-
A.
Uttigen
Uttigen is a small municipality in the canton of Bern, Switzerland, situated along the Aare River between Bern and Thun.
-
B.
Gunalda
Gunalda is a small rural town in Queensland, Australia, situated inland within the Fraser Coast Region and known for its agricultural surroundings and local community facilities.
-
C.
Uttran
Uttran is a residential locality in Botkyrka Municipality within the Stockholm County area of Sweden.
-
D.
Urft
Urft is a river in western Germany that flows through the Eifel region and feeds into the Rur (Roer) River.
-
E.
Urstein
Urstein is a locality in the municipality of Puch bei Hallein in the Austrian state of Salzburg, known for hosting the Salzburg University of Applied Sciences campus.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7046048688190a6cbc64e82b58eca |
completed | March 27, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7ee407881908e591d216c504b24 |
completed | March 29, 2026, 6:34 a.m. |
| NEDg | Description generation | batch_69c8c8b84f88819086ecd371b62e2b5b |
completed | March 29, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8c917a1308190ab2c8e70d6ed8c0e |
completed | March 29, 2026, 6:39 a.m. |
Created at: March 27, 2026, 4:11 p.m.