Triple
T9068895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharks (West Side Story) |
E217311
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object |
Chino (West Side Story)
Chino is a character in West Side Story, a member of the Puerto Rican gang who becomes central to the tragic climax of the musical.
|
E776061
|
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: Chino (West Side Story) | Statement: [Sharks (West Side Story), member, Chino (West Side Story)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chino (West Side Story) Context triple: [Sharks (West Side Story), member, Chino (West Side Story)]
-
A.
Joaquín Toesca
Joaquín Toesca was an 18th-century Italian-born architect who became a key figure in Chilean neoclassical architecture.
-
B.
Cinco
Cinco is a stand-up comedy special and album by Jim Gaffigan featuring his trademark observational and self-deprecating humor.
-
C.
Lucho
Lucho is the commonly used nickname of Luis Enrique, the former Spanish footballer and current football manager.
-
D.
Dizzy Flores
Dizzy Flores is a prominent Mobile Infantry soldier and close companion of Johnny Rico in the military science fiction universe of Starship Troopers.
-
E.
Rosario
Rosario is a feminine given name of Spanish and Italian origin, commonly associated with the Roman Catholic devotion to the Rosary.
- 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: Chino (West Side Story) Triple: [Sharks (West Side Story), member, Chino (West Side Story)]
Generated description
Chino is a character in West Side Story, a member of the Puerto Rican gang who becomes central to the tragic climax of the musical.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chino (West Side Story) Target entity description: Chino is a character in West Side Story, a member of the Puerto Rican gang who becomes central to the tragic climax of the musical.
-
A.
Joaquín Toesca
Joaquín Toesca was an 18th-century Italian-born architect who became a key figure in Chilean neoclassical architecture.
-
B.
Cinco
Cinco is a stand-up comedy special and album by Jim Gaffigan featuring his trademark observational and self-deprecating humor.
-
C.
Lucho
Lucho is the commonly used nickname of Luis Enrique, the former Spanish footballer and current football manager.
-
D.
Dizzy Flores
Dizzy Flores is a prominent Mobile Infantry soldier and close companion of Johnny Rico in the military science fiction universe of Starship Troopers.
-
E.
Rosario
Rosario is a feminine given name of Spanish and Italian origin, commonly associated with the Roman Catholic devotion to the Rosary.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc955ba250819085fa49e0059d06c1 |
completed | April 1, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffddc5c288190b18c2ae1aece4ed6 |
completed | April 3, 2026, 5:50 p.m. |
| NEDg | Description generation | batch_69d000d2c5688190b014ce33c04ff875 |
completed | April 3, 2026, 6:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d001a1056c819083793547dbd4b1ee |
completed | April 3, 2026, 6:06 p.m. |
Created at: March 30, 2026, 7:11 p.m.