Triple
T9117359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Signs |
E218752
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Officer Paski
Officer Paski is a minor law enforcement character appearing in the animated television series "Signs."
|
E779815
|
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: Officer Paski | Statement: [Signs, character, Officer Paski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Officer Paski Context triple: [Signs, character, Officer Paski]
-
A.
Officer Anderson
Officer Anderson is a fictional law enforcement character played by actor Michael Biehn.
-
B.
Officer John Hunton
Officer John Hunton is the main police detective protagonist in the 1995 horror film "The Mangler," who investigates a series of gruesome deaths linked to a possessed industrial laundry machine.
-
C.
Officer Dee Dee
Officer Dee Dee is a recurring police officer character in the animated TV series "Family Guy," serving on the Quahog police force.
-
D.
Officer Pete Malloy
Officer Pete Malloy is a fictional Los Angeles police officer and one of the two main protagonists in the classic TV series "Adam-12."
-
E.
Officer Bill Gannon
Officer Bill Gannon is a fictional Los Angeles police officer and Joe Friday’s partner on the television series "Dragnet," portrayed by actor Harry Morgan.
- 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: Officer Paski Triple: [Signs, character, Officer Paski]
Generated description
Officer Paski is a minor law enforcement character appearing in the animated television series "Signs."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Officer Paski Target entity description: Officer Paski is a minor law enforcement character appearing in the animated television series "Signs."
-
A.
Officer Anderson
Officer Anderson is a fictional law enforcement character played by actor Michael Biehn.
-
B.
Officer John Hunton
Officer John Hunton is the main police detective protagonist in the 1995 horror film "The Mangler," who investigates a series of gruesome deaths linked to a possessed industrial laundry machine.
-
C.
Officer Dee Dee
Officer Dee Dee is a recurring police officer character in the animated TV series "Family Guy," serving on the Quahog police force.
-
D.
Officer Pete Malloy
Officer Pete Malloy is a fictional Los Angeles police officer and one of the two main protagonists in the classic TV series "Adam-12."
-
E.
Officer Bill Gannon
Officer Bill Gannon is a fictional Los Angeles police officer and Joe Friday’s partner on the television series "Dragnet," portrayed by actor Harry Morgan.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8a5e2ac8190b602ef0c77deb2fa |
completed | April 1, 2026, 5:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0307299ec8190acade4f388642e23 |
completed | April 3, 2026, 9:26 p.m. |
| NEDg | Description generation | batch_69d034941af48190b612bdeb4e2a1648 |
completed | April 3, 2026, 9:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d035250d1481908a7a0e108360192e |
completed | April 3, 2026, 9:46 p.m. |
Created at: March 30, 2026, 7:17 p.m.