Triple
T279990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Servant of the People (TV series) |
E5330
|
entity |
| Predicate | targetOfSatire |
P815
|
FINISHED |
| Object | politicians |
—
|
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: politicians | Statement: [Servant of the People (TV series), targetOfSatire, politicians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfSatire Context triple: [Servant of the People (TV series), targetOfSatire, politicians]
-
A.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
titleAlludesTo
Indicates that one title makes an indirect or suggestive reference to the content, theme, or another work associated with the other.
-
C.
derogatesFrom
Indicates that one entity diminishes, belittles, or detracts from the value, reputation, or importance of another entity.
-
D.
primaryTarget
chosen
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
E.
criticizedFor
Indicates that one entity expresses disapproval or negative judgment of another entity specifically because of a particular action, quality, or outcome.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25def95c48190bb8ab2259f67b583 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b765f488190b2cbe4b45cd42821 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.