Triple
T27608444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Violet Baudelaire |
E700244
|
entity |
| Predicate | definingHabit |
P41014
|
FINISHED |
| Object | tying her hair up in a ribbon when inventing |
—
|
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: tying her hair up in a ribbon when inventing | Statement: [Violet Baudelaire, definingHabit, tying her hair up in a ribbon when inventing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definingHabit Context triple: [Violet Baudelaire, definingHabit, tying her hair up in a ribbon when inventing]
-
A.
habitNumber
Indicates a numerical designation or identifier assigned to a particular habit within a set or sequence of habits.
-
B.
hasHabit
chosen
Indicates that an entity regularly performs, practices, or exhibits a particular behavior or routine.
-
C.
modernHabit
Indicates a habit or practice that is characteristic of contemporary or present-day lifestyles or behavior.
-
D.
healthHabit
Indicates a relationship where an entity regularly engages in a behavior or practice that affects its health or well-being.
-
E.
replacedHabitWith
Indicates that one habit has been discontinued and substituted by another habit.
- 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_69ef6a4e2e208190b63b7268f405785c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 27, 2026, 2:10 p.m.