Triple
T15534870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumalee |
E370314
|
entity |
| Predicate | dialogueTheme |
P55704
|
FINISHED |
| Object | mortality |
—
|
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: mortality | Statement: [Lumalee, dialogueTheme, mortality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogueTheme Context triple: [Lumalee, dialogueTheme, mortality]
-
A.
typicalDialogueTheme
Indicates the usual or characteristic subject matter that conversations or dialogues between the entities tend to focus on.
-
B.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
C.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
D.
communicationTheme
chosen
Indicates that a communication centers around, focuses on, or is primarily about a particular topic or theme.
-
E.
dialogueWith
Indicates that two entities are engaged in a mutual conversational exchange or dialogue with each other.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442e327c8190b4b879c8a3cd38e3 |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:06 a.m.