Triple
T4913333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palamedes |
E110285
|
entity |
| Predicate | hasCensorshipStatus |
P12717
|
FINISHED |
| Object | politically sensitive in the Dutch 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: politically sensitive in the Dutch Republic | Statement: [Palamedes, hasCensorshipStatus, politically sensitive in the Dutch Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCensorshipStatus Context triple: [Palamedes, hasCensorshipStatus, politically sensitive in the Dutch Republic]
-
A.
hasCensorshipHistory
Indicates that an entity has previously been subject to censorship or involved in acts of censoring content.
-
B.
revisedVersionCensorshipStatus
Indicates the censorship or restriction status applied to a revised version of some original content.
-
C.
censorshipStatusAtTime
Indicates the censorship status of something at a specific point in time, capturing whether and how it was censored then.
-
D.
censorshipReason
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
E.
hasStatusLabel
chosen
Indicates that an entity is associated with a specific status expressed as a human-readable label.
- 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e9dc41481908c0c398852e6819c |
completed | March 20, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69bd6c325e188190823836d79934e9bc |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:29 p.m.