Triple
T9592794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fool for Love |
E231455
|
entity |
| Predicate | hasDialogueFeature |
P31437
|
FINISHED |
| Object | overlapping dialogue |
—
|
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: overlapping dialogue | Statement: [Fool for Love, hasDialogueFeature, overlapping dialogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialogueFeature Context triple: [Fool for Love, hasDialogueFeature, overlapping dialogue]
-
A.
hasDialogueTrait
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
B.
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).
-
C.
hasProseDialogue
Indicates that one entity contains or features spoken or conversational content expressed in prose form involving another entity.
-
D.
hasNoSpokenDialogue
Indicates that the referenced entity does not produce any spoken dialogue within the given context or work.
-
E.
dialogueType
chosen
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a11ec7081908dc580de2f369706 |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:07 p.m.