Triple
T11546382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moneybags |
E273784
|
entity |
| Predicate | typicalDialogueTheme |
P100033
|
FINISHED |
| Object | money |
—
|
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: money | Statement: [Moneybags, typicalDialogueTheme, money]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDialogueTheme Context triple: [Moneybags, typicalDialogueTheme, money]
-
A.
typicalDialogueStyle
Indicates the characteristic manner or pattern in which an entity typically communicates or conducts dialogue.
-
B.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
C.
dialoguesBy
Indicates that one entity is the creator, author, or source of the dialogues associated with another entity.
-
D.
dialogueDynamic
Indicates a relationship where entities are engaged in or contributing to an evolving, back-and-forth dialogue or conversational exchange.
-
E.
dramaticTheme
Indicates that a work, scene, or narrative centers around a particular dramatic subject, motif, or emotional conflict as its main thematic focus.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d886e3ad548190b2c88332f5d919bd |
completed | April 10, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69d8087cbe7c819085680f3d67ccc978 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:37 p.m.