Triple
T5128977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suchitra Sen |
E115648
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Harano Sur
Harano Sur is a classic Bengali romantic drama film starring Suchitra Sen, celebrated for its poignant love story and memorable music.
|
E496027
|
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: Harano Sur | Statement: [Suchitra Sen, notableWork, Harano Sur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harano Sur Context triple: [Suchitra Sen, notableWork, Harano Sur]
-
A.
Haruna
Haruna was a Japanese Kongō-class fast battleship that served in the Imperial Japanese Navy during both World Wars and saw extensive action in the Pacific Theater.
-
B.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
-
C.
Masatake
Masatake is a Japanese masculine given name that has been borne by various notable figures, including military and political leaders.
-
D.
Sakae
Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
-
E.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
- 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: Harano Sur Triple: [Suchitra Sen, notableWork, Harano Sur]
Generated description
Harano Sur is a classic Bengali romantic drama film starring Suchitra Sen, celebrated for its poignant love story and memorable music.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harano Sur Target entity description: Harano Sur is a classic Bengali romantic drama film starring Suchitra Sen, celebrated for its poignant love story and memorable music.
-
A.
Haruna
Haruna was a Japanese Kongō-class fast battleship that served in the Imperial Japanese Navy during both World Wars and saw extensive action in the Pacific Theater.
-
B.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
-
C.
Masatake
Masatake is a Japanese masculine given name that has been borne by various notable figures, including military and political leaders.
-
D.
Sakae
Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
-
E.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
- 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7825facc8190b2a6c17216290b5c |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4c23d5c8190883a297254d9c80d |
completed | March 21, 2026, 4:18 p.m. |
| NEDg | Description generation | batch_69bec6620aac8190a820190e7facd70a |
completed | March 21, 2026, 4:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bec70062f48190baae277e6f8c5c4e |
completed | March 21, 2026, 4:27 p.m. |
Created at: March 20, 2026, 1:42 p.m.