Triple
T18736615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Christie |
E458178
|
entity |
| Predicate | usedForComicEffect |
P114828
|
FINISHED |
| Object | relationship neuroses |
—
|
LITERAL FINISHED |
How this triple was built (2 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: relationship neuroses | Statement: [Jane Christie, usedForComicEffect, relationship neuroses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForComicEffect Context triple: [Jane Christie, usedForComicEffect, relationship neuroses]
-
A.
comicFunction
Indicates a relationship where something serves a humorous or entertainment role, such as providing comedy, comic relief, or a joking purpose within a context.
-
B.
usedForHumor
chosen
Indicates that something is employed with the intention of being funny, amusing, or comical.
-
C.
usedByCharacter
Indicates that something (such as an item, ability, or resource) is utilized or employed by a particular character.
-
D.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
-
E.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
- F. None of above.
Provenance (3 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e57689fa508190ad821d361cba9edf |
completed | April 20, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:51 a.m.