Triple
T21945131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vijaypath |
E541913
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Karan
Karan is a central character in the 1994 Hindi action film "Vijaypath," portrayed as a determined and justice-seeking protagonist.
|
E1509507
|
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: Karan | Statement: [Vijaypath, featuresCharacter, Karan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karan Context triple: [Vijaypath, featuresCharacter, Karan]
-
A.
Karan
Karan is the given first name of Lord Bilimoria, a prominent British-Indian entrepreneur and life peer.
-
B.
Karan Pol
Karan Pol is a historic gateway that serves as one of the principal entrances to Junagarh Fort in Bikaner, Rajasthan, India.
-
C.
Khem Karan
Khem Karan is a small border town in the Tarn Taran district of Punjab, India, known for its proximity to the India–Pakistan border and its role in the 1965 Indo-Pak war.
-
D.
Kovai
Kovai is the commonly used local name for Coimbatore, a major industrial and educational city in the South Indian state of Tamil Nadu.
-
E.
Karamlesh
Karamlesh is a historic Assyrian Christian town in northern Iraq’s Nineveh Plains, known for its ancient churches and proximity to Mosul.
- 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: Karan Triple: [Vijaypath, featuresCharacter, Karan]
Generated description
Karan is a central character in the 1994 Hindi action film "Vijaypath," portrayed as a determined and justice-seeking protagonist.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karan Target entity description: Karan is a central character in the 1994 Hindi action film "Vijaypath," portrayed as a determined and justice-seeking protagonist.
-
A.
Karan
Karan is the given first name of Lord Bilimoria, a prominent British-Indian entrepreneur and life peer.
-
B.
Karan Pol
Karan Pol is a historic gateway that serves as one of the principal entrances to Junagarh Fort in Bikaner, Rajasthan, India.
-
C.
Khem Karan
Khem Karan is a small border town in the Tarn Taran district of Punjab, India, known for its proximity to the India–Pakistan border and its role in the 1965 Indo-Pak war.
-
D.
Kovai
Kovai is the commonly used local name for Coimbatore, a major industrial and educational city in the South Indian state of Tamil Nadu.
-
E.
Karamlesh
Karamlesh is a historic Assyrian Christian town in northern Iraq’s Nineveh Plains, known for its ancient churches and proximity to Mosul.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a60f1f49c81909f6c17dad3bd0219 |
completed | May 18, 2026, 12:44 a.m. |
| NEDg | Description generation | batch_6a0a6200fb1c81909a4ab05fd368dafc |
completed | May 18, 2026, 12:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a626731d8819097b209ae1375ae25 |
completed | May 18, 2026, 12:50 a.m. |
Created at: April 16, 2026, 7:56 p.m.