Triple
T19985084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azkaban |
E493911
|
entity |
| Predicate | knownEffectOnInmates |
P83128
|
FINISHED |
| Object | gradual loss of happiness |
—
|
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: gradual loss of happiness | Statement: [Azkaban, knownEffectOnInmates, gradual loss of happiness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownEffectOnInmates Context triple: [Azkaban, knownEffectOnInmates, gradual loss of happiness]
-
A.
effectOnPrisoners
chosen
Indicates the impact or consequences that something has on prisoners.
-
B.
inmates
Indicates that one entity is confined or held as a prisoner within an institution or facility associated with another entity.
-
C.
securityForInmates
Indicates the provision or management of protective measures and safeguards specifically intended for inmates.
-
D.
usedForImprisoning
Indicates that something serves as a means, tool, or method for confining or detaining someone against their will.
-
E.
hasNotableCategoryOfPrisoners
Indicates that a prison is known for housing a specific, notable category or type of prisoners.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d162b008190a18d325796d75d77 |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:29 p.m.