Triple
T25708617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Grenzpolizei |
E644667
|
entity |
| Predicate | hasOpposedActivity |
P165316
|
FINISHED |
| Object | flight from the republic |
—
|
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: flight from the republic | Statement: [Deutsche Grenzpolizei, hasOpposedActivity, flight from the republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposedActivity Context triple: [Deutsche Grenzpolizei, hasOpposedActivity, flight from the republic]
-
A.
hasOpposedCondition
Indicates that one condition stands in direct opposition or contradiction to another condition.
-
B.
hasPoliticalActivityIn
Indicates that an entity engages in or is associated with political activities within a specified location or jurisdiction.
-
C.
hasActivityIn
Indicates that an entity engages in or performs a particular activity within a specified context, location, or domain.
-
D.
hasOpposedParty
Indicates that one party is in an opposing or adversarial position relative to another party, typically within a dispute, conflict, or legal proceeding.
-
E.
hasOppositionType
Indicates that an entity is associated with a specific kind or category of opposition it faces or represents.
- F. None of above. chosen
Provenance (4 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f658a91ba0819084fbe3dd8a09f7cd |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f657f2c8b08190bfeb3173ef78207d |
completed | May 2, 2026, 8 p.m. |
Created at: April 21, 2026, 9:08 p.m.