Triple
T13930581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almost Christmas |
E334978
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Alkesh Parmar
Alkesh Parmar is a film editor known for his work on the holiday comedy-drama movie "Almost Christmas."
|
E1069866
|
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: Alkesh Parmar | Statement: [Almost Christmas, editedBy, Alkesh Parmar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alkesh Parmar Context triple: [Almost Christmas, editedBy, Alkesh Parmar]
-
A.
Bhavit Sheth
Bhavit Sheth is an Indian entrepreneur best known as the co-founder of Dream Sports, the parent company of fantasy sports platform Dream11.
-
B.
Koli Patel
Koli Patel is a subgroup of the Kolis, a traditional coastal and agrarian community primarily found in western India.
-
C.
Anish Savjani
Anish Savjani is an American film producer known for his work on acclaimed independent films, including the thriller "Green Room."
-
D.
Harish Patel
Harish Patel is an Indian character actor known for his extensive work in Hindi cinema and television, as well as for appearing in international projects such as Marvel’s Eternals.
-
E.
Naren Patel
Naren Patel is a notable individual distinguished by achievements significant enough to be specifically recognized among people with the surname Patel.
- 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: Alkesh Parmar Triple: [Almost Christmas, editedBy, Alkesh Parmar]
Generated description
Alkesh Parmar is a film editor known for his work on the holiday comedy-drama movie "Almost Christmas."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alkesh Parmar Target entity description: Alkesh Parmar is a film editor known for his work on the holiday comedy-drama movie "Almost Christmas."
-
A.
Bhavit Sheth
Bhavit Sheth is an Indian entrepreneur best known as the co-founder of Dream Sports, the parent company of fantasy sports platform Dream11.
-
B.
Koli Patel
Koli Patel is a subgroup of the Kolis, a traditional coastal and agrarian community primarily found in western India.
-
C.
Anish Savjani
Anish Savjani is an American film producer known for his work on acclaimed independent films, including the thriller "Green Room."
-
D.
Harish Patel
Harish Patel is an Indian character actor known for his extensive work in Hindi cinema and television, as well as for appearing in international projects such as Marvel’s Eternals.
-
E.
Naren Patel
Naren Patel is a notable individual distinguished by achievements significant enough to be specifically recognized among people with the surname Patel.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf13b2881908a48058a719d3745 |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce8262288190a7e6dd647b1917c1 |
completed | May 3, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69f9fd5b82f48190b0b89ddca25883cc |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f9fea0a9dc8190b5b65dfec9626949 |
completed | May 5, 2026, 2:28 p.m. |
Created at: April 9, 2026, 10:16 p.m.