Triple
T870230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nausicaa |
E18792
|
entity |
| Predicate | activityAtFirstMeeting |
P8834
|
FINISHED |
| Object | washing clothes with her maidservants |
—
|
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: washing clothes with her maidservants | Statement: [Nausicaa, activityAtFirstMeeting, washing clothes with her maidservants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activityAtFirstMeeting Context triple: [Nausicaa, activityAtFirstMeeting, washing clothes with her maidservants]
-
A.
firstMeetingSeason
Indicates the season of the year during which two entities first met.
-
B.
firstAssemblyMeeting
Indicates that an entity is the initial or inaugural meeting of a particular assembly or deliberative body.
-
C.
activityType
chosen
Indicates the specific kind or category of action or event that an entity is engaged in or associated with.
-
D.
socialFunction
Indicates that an entity serves a particular role, purpose, or activity within a social context or gathering.
-
E.
meetingType
Indicates the specific category or format of a meeting that characterizes how it is organized or conducted.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac94d5ac81909feee876696da589 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa89ca008190b50d061ac7fe19f9 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.