Triple
T36610386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nampeyo |
E903448
|
entity |
| Predicate | workshopWith |
P97828
|
FINISHED |
| Object | her husband Lesou |
—
|
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: her husband Lesou | Statement: [Nampeyo, workshopWith, her husband Lesou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workshopWith Context triple: [Nampeyo, workshopWith, her husband Lesou]
-
A.
workshopMark
Indicates that an entity has been designated, labeled, or flagged in the context of a workshop-related process or activity.
-
B.
workshopInTitleIndicates
Indicates that the presence of the word "workshop" in a title signifies that the associated event, session, or item is a workshop.
-
C.
notableWorkshop
Indicates that an entity is a workshop distinguished by particular significance, prominence, or recognition (e.g., in impact, reputation, or importance).
-
D.
workshopOrStudio
Indicates that one entity functions as a workshop or studio associated with, used by, or belonging to another entity.
-
E.
workWith
chosen
Indicates that one entity collaborates or engages in work-related activities together with another entity.
- 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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:11 p.m.