Triple
T29434809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bank casino |
E746539
|
entity |
| Predicate | ownerCharacterization |
P174289
|
FINISHED |
| Object | ruthless |
—
|
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: ruthless | Statement: [The Bank casino, ownerCharacterization, ruthless]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ownerCharacterization Context triple: [The Bank casino, ownerCharacterization, ruthless]
-
A.
stanceCharacterization
Indicates how an entity’s attitude, position, or viewpoint toward another entity, claim, or issue is characterized.
-
B.
posterCharacterizes
Indicates that a poster visually or textually portrays and defines the qualities, traits, or identity of something or someone.
-
C.
titleCharacterization
Indicates how a title characterizes, describes, or frames an associated entity (such as a work, person, or concept).
-
D.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
E.
AICharacteristics
Indicates the defining traits, behaviors, or properties that characterize an artificial intelligence system.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 28, 2026, 3:15 p.m.