Triple
T302201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gypsies |
E6221
|
entity |
| Predicate | discouragedIn |
P2184
|
FINISHED |
| Object | academic writing |
—
|
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: academic writing | Statement: [Gypsies, discouragedIn, academic writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discouragedIn Context triple: [Gypsies, discouragedIn, academic writing]
-
A.
discourages
chosen
Indicates an action or influence that deters, dissuades, or reduces the likelihood of someone performing a particular behavior or pursuing a certain outcome.
-
B.
prohibits
Indicates that one entity forbids or disallows another entity from performing a specific action or being in a certain state.
-
C.
encourages
Indicates actively motivating, supporting, or giving confidence to another entity to pursue an action, behavior, or state.
-
D.
discriminatedAgainst
Indicates that one entity treats another unfairly or unequally based on a particular characteristic, such as race, gender, or other protected attributes.
-
E.
derogatesFrom
Indicates that one entity diminishes, belittles, or detracts from the value, reputation, or importance of another entity.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93c367881908d3f6e2b81d44d7f |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.