Triple
T11754219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catch-22 |
E279483
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Doc Daneeka
Doc Daneeka is the cynical, self-interested army flight surgeon in Joseph Heller’s novel "Catch-22," known for his darkly comic outlook on war and bureaucracy.
|
E945042
|
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: Doc Daneeka | Statement: [Catch-22, mainCharacter, Doc Daneeka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doc Daneeka Context triple: [Catch-22, mainCharacter, Doc Daneeka]
-
A.
Dedra Meero
Dedra Meero is an ambitious and ruthless Imperial Security Bureau officer in the Star Wars series "Andor," known for her methodical pursuit of rebel activity.
-
B.
Darel
Darel is a given name, typically a variant spelling of Daryl, used for both males and females.
-
C.
Doctor T’Ana
Doctor T’Ana is a gruff, no-nonsense Caitian chief medical officer known for her abrasive humor and competence in the animated series Star Trek: Lower Decks.
-
D.
Rachel Zane
Rachel Zane is a central character in the legal drama series "Suits," known as a talented paralegal who aspires to become a lawyer and develops a key romantic relationship with Mike Ross.
-
E.
Dettah
Dettah is a small Dene First Nations community located near Yellowknife in the Northwest Territories of Canada.
- 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: Doc Daneeka Triple: [Catch-22, mainCharacter, Doc Daneeka]
Generated description
Doc Daneeka is the cynical, self-interested army flight surgeon in Joseph Heller’s novel "Catch-22," known for his darkly comic outlook on war and bureaucracy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Doc Daneeka Target entity description: Doc Daneeka is the cynical, self-interested army flight surgeon in Joseph Heller’s novel "Catch-22," known for his darkly comic outlook on war and bureaucracy.
-
A.
Dedra Meero
Dedra Meero is an ambitious and ruthless Imperial Security Bureau officer in the Star Wars series "Andor," known for her methodical pursuit of rebel activity.
-
B.
Darel
Darel is a given name, typically a variant spelling of Daryl, used for both males and females.
-
C.
Doctor T’Ana
Doctor T’Ana is a gruff, no-nonsense Caitian chief medical officer known for her abrasive humor and competence in the animated series Star Trek: Lower Decks.
-
D.
Rachel Zane
Rachel Zane is a central character in the legal drama series "Suits," known as a talented paralegal who aspires to become a lawyer and develops a key romantic relationship with Mike Ross.
-
E.
Dettah
Dettah is a small Dene First Nations community located near Yellowknife in the Northwest Territories of Canada.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a50b8a14819092a7397d73f0a8e3 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f01a21559c819097d0287dd8e2f411 |
completed | April 28, 2026, 2:23 a.m. |
| NEDg | Description generation | batch_69f0319622c48190bee6c906f08c0a8c |
completed | April 28, 2026, 4:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f05ad36e4c8190b7239e5b33713369 |
completed | April 28, 2026, 6:59 a.m. |
Created at: April 8, 2026, 9:41 p.m.