Triple
T16528040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zarina Wahab |
E401489
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Ek Ghar
Ek Ghar is an Indian film best known for featuring actress Zarina Wahab in a prominent role.
|
E1218737
|
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: Ek Ghar | Statement: [Zarina Wahab, notableWork, Ek Ghar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ek Ghar Context triple: [Zarina Wahab, notableWork, Ek Ghar]
-
A.
Spin Ghar
Spin Ghar is a prominent mountain range in eastern Afghanistan forming part of the border with Pakistan and known for its rugged, high peaks.
-
B.
Rang Ghar
Rang Ghar is an 18th-century royal sports pavilion and amphitheater in Assam, India, historically used by Ahom kings to watch traditional games and cultural events.
-
C.
Ghari
Ghari is an Oceanic language spoken in the Solomon Islands, belonging to the Meso-Melanesian branch of the Austronesian language family.
-
D.
Ghum
Ghum is a small hill station in West Bengal, India, known for its high-altitude railway station on the Darjeeling Himalayan Railway and its scenic views of the surrounding Himalayas.
-
E.
Salim Singh Ki Haveli
Salim Singh Ki Haveli is an ornately carved historic mansion in Jaisalmer, Rajasthan, famed for its distinctive architecture and intricate stonework.
- 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: Ek Ghar Triple: [Zarina Wahab, notableWork, Ek Ghar]
Generated description
Ek Ghar is an Indian film best known for featuring actress Zarina Wahab in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ek Ghar Target entity description: Ek Ghar is an Indian film best known for featuring actress Zarina Wahab in a prominent role.
-
A.
Spin Ghar
Spin Ghar is a prominent mountain range in eastern Afghanistan forming part of the border with Pakistan and known for its rugged, high peaks.
-
B.
Rang Ghar
Rang Ghar is an 18th-century royal sports pavilion and amphitheater in Assam, India, historically used by Ahom kings to watch traditional games and cultural events.
-
C.
Ghari
Ghari is an Oceanic language spoken in the Solomon Islands, belonging to the Meso-Melanesian branch of the Austronesian language family.
-
D.
Ghum
Ghum is a small hill station in West Bengal, India, known for its high-altitude railway station on the Darjeeling Himalayan Railway and its scenic views of the surrounding Himalayas.
-
E.
Salim Singh Ki Haveli
Salim Singh Ki Haveli is an ornately carved historic mansion in Jaisalmer, Rajasthan, famed for its distinctive architecture and intricate stonework.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed57be481908625d4c5aab0940c |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00608efd0c81908e64419bd74eb285 |
completed | May 10, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_6a0062cbe9048190823db47a42dac26a |
completed | May 10, 2026, 10:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00635f57c08190ad915082b00b0f88 |
completed | May 10, 2026, 10:52 a.m. |
Created at: April 10, 2026, 5:14 a.m.