Triple
T13568645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nausea |
E324101
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Anny
Anny is a character from Jean-Paul Sartre’s novel "Nausea," serving as a significant figure from the protagonist Roquentin’s past and embodying themes of memory, lost possibilities, and existential disillusionment.
|
E1050490
|
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: Anny | Statement: [Nausea, hasCharacter, Anny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anny Context triple: [Nausea, hasCharacter, Anny]
-
A.
Annis
Annis is a feminine given name of English origin, historically used in the Anglophone world.
-
B.
Annie Roland
Annie Roland is a fictional nurse featured as a character in the American television drama series "Nurses."
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
-
E.
Arnella
Arnella is a feminine given name, notably borne by Arnella Flynn, the daughter of actor Errol Flynn.
- 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: Anny Triple: [Nausea, hasCharacter, Anny]
Generated description
Anny is a character from Jean-Paul Sartre’s novel "Nausea," serving as a significant figure from the protagonist Roquentin’s past and embodying themes of memory, lost possibilities, and existential disillusionment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anny Target entity description: Anny is a character from Jean-Paul Sartre’s novel "Nausea," serving as a significant figure from the protagonist Roquentin’s past and embodying themes of memory, lost possibilities, and existential disillusionment.
-
A.
Annis
Annis is a feminine given name of English origin, historically used in the Anglophone world.
-
B.
Annie Roland
Annie Roland is a fictional nurse featured as a character in the American television drama series "Nurses."
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
-
E.
Arnella
Arnella is a feminine given name, notably borne by Arnella Flynn, the daughter of actor Errol Flynn.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00e0188819094fde44f85adb69c |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f8967288190b822ed1e115f85b2 |
completed | May 3, 2026, 5:02 p.m. |
| NEDg | Description generation | batch_69f78125632881908d601ee4c4aaae35 |
completed | May 3, 2026, 5:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f781e32cb48190abc83e65405ac8ac |
completed | May 3, 2026, 5:12 p.m. |
Created at: April 9, 2026, 9:48 p.m.