Triple
T11236173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Certified Copy |
E265945
|
entity |
| Predicate | hasMultilingualDialogue |
P98605
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Certified Copy, hasMultilingualDialogue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultilingualDialogue Context triple: [Certified Copy, hasMultilingualDialogue, true]
-
A.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
-
B.
hasDialogueTrait
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
C.
isMultilingual
Indicates that an entity can understand and/or communicate in multiple languages.
-
D.
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).
-
E.
hasProseDialogue
Indicates that one entity contains or features spoken or conversational content expressed in prose form involving another entity.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e904cf888190826fc964f76b5cb2 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
| PDg | Predicate description generation | batch_69d796cf74308190a5b29d0dd82954a2 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:30 p.m.