Triple
T14476730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Act Without Words I |
E358991
|
entity |
| Predicate | dialogue |
P114797
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Act Without Words I, dialogue, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogue Context triple: [Act Without Words I, dialogue, none]
-
A.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
B.
dialogueDynamic
Indicates a relationship where entities are engaged in or contributing to an evolving, back-and-forth dialogue or conversational exchange.
-
C.
dialogueWith
Indicates that two entities are engaged in a mutual conversational exchange or dialogue with each other.
-
D.
dialoguesBy
Indicates that one entity is the creator, author, or source of the dialogues associated with another entity.
-
E.
dialogueContext
Indicates the situational and conversational background in which a dialogue occurs, including prior exchanges and relevant circumstances that shape its interpretation.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9248edb48190a74eb032aeaac027 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de610330a48190b558235a14c0dc9f |
completed | April 14, 2026, 3:45 p.m. |
Created at: April 10, 2026, 1:20 a.m.