Triple
T38364415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Queen’s Comedy |
E892394
|
entity |
| Predicate | hasDialogueCharacteristic |
P85534
|
FINISHED |
| Object | witty |
—
|
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: witty | Statement: [The Queen’s Comedy, hasDialogueCharacteristic, witty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialogueCharacteristic Context triple: [The Queen’s Comedy, hasDialogueCharacteristic, witty]
-
A.
hasDialogueTrait
chosen
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
B.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
-
C.
hasDialogueSystem
Indicates that an entity includes or is equipped with a system for managing dialogue or conversational interactions.
-
D.
hasDialogueAbout
Indicates that one entity engages in dialogue or conversation concerning the topic, subject, or entity specified by the other.
-
E.
hasDialogueFunction
Indicates that an utterance or segment of discourse serves a specific communicative role or function within a dialogue (e.g., question, answer, request, acknowledgment).
- 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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffc3f0b19c8190b5a749bc3cad21dd |
completed | May 9, 2026, 11:32 p.m. |
| PD | Predicate disambiguation | batch_69ffc1b882808190932b2d43ea5537c9 |
completed | May 9, 2026, 11:22 p.m. |
Created at: May 3, 2026, 4:31 p.m.