Triple
T35694134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lena Doyle |
E1031385
|
entity |
| Predicate | opposesAction |
P437
|
FINISHED |
| Object | corporate takeover of her land |
—
|
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: corporate takeover of her land | Statement: [Lena Doyle, opposesAction, corporate takeover of her land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposesAction Context triple: [Lena Doyle, opposesAction, corporate takeover of her land]
-
A.
opposedBy
chosen
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
B.
opposesLabel
Indicates that one entity expresses disagreement with, resistance to, or active opposition against another entity or its position.
-
C.
opposedBecause
Indicates that one entity is opposed to another specifically due to a particular reason, cause, or justification.
-
D.
opposesEffectOf
Indicates that one entity counteracts, reduces, or nullifies the effect produced by another entity.
-
E.
opposedDuring
Indicates that one entity actively resisted or was in conflict with another entity during a specified time period or event.
- 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_69f76e0c73ec819080ab60a9e2f5f1f6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd5bf69acc819092a01e4259785dc3 |
completed | May 8, 2026, 3:43 a.m. |
| PD | Predicate disambiguation | batch_69fd59b3f4ac8190a7f9dd3142da6e09 |
completed | May 8, 2026, 3:34 a.m. |
Created at: May 3, 2026, 4:05 p.m.