Triple

T13795703
Position Surface form Disambiguated ID Type / Status
Subject Like Water for Chocolate E331507 entity
Predicate producer P490 FINISHED
Object Ynot
Ynot is a film production company known for its work on the acclaimed Mexican romantic drama "Like Water for Chocolate."
 E1062929 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: Ynot | Statement: [Like Water for Chocolate, producer, Ynot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ynot
Context triple: [Like Water for Chocolate, producer, Ynot]
  • A. Notsi
    Notsi is an Oceanic language spoken in parts of Papua New Guinea, belonging to the Meso-Melanesian branch of the Austronesian language family.
  • B. Noth
    Noth is a surname most prominently associated with American actor Chris Noth, known for his roles in television series such as "Sex and the City" and "Law & Order."
  • C. Nebelong
    Nebelong is a Danish surname most notably associated with 19th-century architect Johan Henrik Nebelong.
  • D. Neyo
    Ne-Yo is an American R&B singer, songwriter, and record producer known for hits like "So Sick" and "Closer" and for writing songs for numerous major artists.
  • E. Elys
    Elys is a variant form of the given name Ellis, used as an alternative spelling or stylistic variation.
  • 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: Ynot
Triple: [Like Water for Chocolate, producer, Ynot]
Generated description
Ynot is a film production company known for its work on the acclaimed Mexican romantic drama "Like Water for Chocolate."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ynot
Target entity description: Ynot is a film production company known for its work on the acclaimed Mexican romantic drama "Like Water for Chocolate."
  • A. Notsi
    Notsi is an Oceanic language spoken in parts of Papua New Guinea, belonging to the Meso-Melanesian branch of the Austronesian language family.
  • B. Noth
    Noth is a surname most prominently associated with American actor Chris Noth, known for his roles in television series such as "Sex and the City" and "Law & Order."
  • C. Nebelong
    Nebelong is a Danish surname most notably associated with 19th-century architect Johan Henrik Nebelong.
  • D. Neyo
    Ne-Yo is an American R&B singer, songwriter, and record producer known for hits like "So Sick" and "Closer" and for writing songs for numerous major artists.
  • E. Elys
    Elys is a variant form of the given name Ellis, used as an alternative spelling or stylistic variation.
  • 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0259b0e4819081c11ced694384fb completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b08508688190b7e8c33e6b65e25d completed May 3, 2026, 8:31 p.m.
NEDg Description generation batch_69f7b48bf704819098bfb70def28a0d1 completed May 3, 2026, 8:48 p.m.
NED2 Entity disambiguation (via description) batch_69f7b5c9e284819094e7af030e1e9034 completed May 3, 2026, 8:53 p.m.
Created at: April 9, 2026, 10:11 p.m.