Triple
T5110905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermione Granger |
E115210
|
entity |
| Predicate | bloodStatusTargetOfPrejudice |
P61632
|
FINISHED |
| Object | Mudblood slur |
—
|
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: Mudblood slur | Statement: [Hermione Granger, bloodStatusTargetOfPrejudice, Mudblood slur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bloodStatusTargetOfPrejudice Context triple: [Hermione Granger, bloodStatusTargetOfPrejudice, Mudblood slur]
-
A.
bloodStatus
Indicates the classification of an entity based on the type or purity of its blood or lineage.
-
B.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
C.
victimStatus
Indicates the condition or state of a person who has been harmed or wronged as a result of an event, action, or offense.
-
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.
hasVictims
Indicates that an entity has one or more individuals who have been harmed, injured, or adversely affected by it.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ad362c8190b9cbded390aaea3c |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:41 p.m.