Triple
T14476486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beckett on Film: Not I |
E358985
|
entity |
| Predicate | dialogueCharacteristics |
P85534
|
FINISHED |
| Object | rapid delivery |
—
|
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: rapid delivery | Statement: [Beckett on Film: Not I, dialogueCharacteristics, rapid delivery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogueCharacteristics Context triple: [Beckett on Film: Not I, dialogueCharacteristics, rapid delivery]
-
A.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
B.
hasDialogueTrait
chosen
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
C.
characterContrast
Indicates a relationship where two characters are compared to highlight their opposing or significantly differing traits, roles, or behaviors.
-
D.
dialogueAppearance
Indicates that one entity appears or is visually represented during a particular dialogue or conversational sequence involving another entity.
-
E.
characterDuet
Indicates a relationship where two characters perform together as a duet in a shared scene, song, or action.
- 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_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. |
Created at: April 10, 2026, 1:20 a.m.