Triple
T3538074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finn |
E74813
|
entity |
| Predicate | notableAlly |
P48198
|
FINISHED |
| Object |
Rose Tico
Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
|
E367911
|
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: Rose Tico | Statement: [Finn, notableAlly, Rose Tico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rose Tico Context triple: [Finn, notableAlly, Rose Tico]
-
A.
Fennec Shand
Fennec Shand is a skilled mercenary and elite assassin in the Star Wars universe who becomes a close ally and enforcer to Boba Fett.
-
B.
Cara Dune
Cara Dune is a former Rebel shock trooper turned mercenary who becomes a key ally to the titular bounty hunter in the Star Wars series "The Mandalorian."
-
C.
Beru
Beru is a low-lying coral atoll in the southern Gilbert Islands of Kiribati, known for its traditional villages, lagoon, and vulnerability to sea-level rise.
-
D.
Charena Swann
Charena Swann is the wife of former NFL star and Pro Football Hall of Famer Lynn Swann.
-
E.
Ahsoka
Ahsoka is a live-action Star Wars television series centered on former Jedi Padawan Ahsoka Tano, continuing her story in the era after the fall of the Empire.
- 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: Rose Tico Triple: [Finn, notableAlly, Rose Tico]
Generated description
Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rose Tico Target entity description: Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
-
A.
Fennec Shand
Fennec Shand is a skilled mercenary and elite assassin in the Star Wars universe who becomes a close ally and enforcer to Boba Fett.
-
B.
Cara Dune
Cara Dune is a former Rebel shock trooper turned mercenary who becomes a key ally to the titular bounty hunter in the Star Wars series "The Mandalorian."
-
C.
Beru
Beru is a low-lying coral atoll in the southern Gilbert Islands of Kiribati, known for its traditional villages, lagoon, and vulnerability to sea-level rise.
-
D.
Charena Swann
Charena Swann is the wife of former NFL star and Pro Football Hall of Famer Lynn Swann.
-
E.
Ahsoka
Ahsoka is a live-action Star Wars television series centered on former Jedi Padawan Ahsoka Tano, continuing her story in the era after the fall of the Empire.
- 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbcc928248190b851f8280d58cfcf |
completed | March 8, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bd4d5f4819095c962f01fc6f7e8 |
completed | March 13, 2026, 4 a.m. |
| NEDg | Description generation | batch_69b38c5cfb608190b451be14246d5481 |
completed | March 13, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38ce0e1688190a7ee3d079fb83f3d |
completed | March 13, 2026, 4:04 a.m. |
Created at: March 8, 2026, 3:20 p.m.