Triple
T14484449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmer children |
E359190
|
entity |
| Predicate | viewedByCharacter |
P21336
|
FINISHED |
| Object | Nora Helmer as her primary responsibility |
—
|
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: Nora Helmer as her primary responsibility | Statement: [Helmer children, viewedByCharacter, Nora Helmer as her primary responsibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewedByCharacter Context triple: [Helmer children, viewedByCharacter, Nora Helmer as her primary responsibility]
-
A.
viewedBy
Indicates that something has been seen, observed, or watched by a particular entity.
-
B.
visitedByCharacter
Indicates that a location or place is visited or physically gone to by a specific character.
-
C.
viewedBySomeAs
chosen
Indicates that at least one observer or group perceives or interprets an entity in a particular way or role.
-
D.
hasViewOfFictional
Indicates that one entity has a visual or conceptual perspective of a fictional entity or scene.
-
E.
characterDisplay
Indicates a relationship where one entity visually presents or renders the appearance or representation of a character or set of characters.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924d7f4c8190b1f62b5ffe1ff649 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.