Triple
T21638923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eve Ensler |
E534034
|
entity |
| Predicate | thematicFocusInWork |
P109058
|
FINISHED |
| Object | women's sexuality |
—
|
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: women's sexuality | Statement: [Eve Ensler, thematicFocusInWork, women's sexuality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thematicFocusInWork Context triple: [Eve Ensler, thematicFocusInWork, women's sexuality]
-
A.
associatedWithWorkTheme
Indicates a relationship where something is connected or related to a particular work theme or subject matter.
-
B.
notableWorkFocus
Indicates that a notable work primarily centers on, addresses, or is significantly concerned with a particular subject, theme, or area.
-
C.
creativeWorkFocus
chosen
Indicates that one entity is the primary subject, theme, or focal point of another entity’s creative work.
-
D.
focusesOnWork
Indicates that an entity directs its attention, effort, or primary activity toward work-related tasks or responsibilities.
-
E.
careerTheme
Indicates a thematic or conceptual connection between an entity and a particular career-related focus, motif, or overarching professional topic.
- 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_69e0c465ae7481908577b7209fdb2a77 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef538fb12481908f70ad8dbe1d99e4 |
completed | April 27, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:35 p.m.