Triple
T3250236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tea Cake |
E68158
|
entity |
| Predicate | deathInStory |
P36869
|
FINISHED |
| Object | dies after contracting rabies |
—
|
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: dies after contracting rabies | Statement: [Tea Cake, deathInStory, dies after contracting rabies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathInStory Context triple: [Tea Cake, deathInStory, dies after contracting rabies]
-
A.
deathInFiction
chosen
Indicates that an entity’s death occurs within a fictional work or narrative rather than in real life.
-
B.
deathDescribedIn
Indicates that a person's death is documented, narrated, or otherwise detailed within a particular source or description.
-
C.
deathApprox
Indicates that an entity’s death occurred at an approximate, rather than exact, time or date.
-
D.
deathDescribedAs
Indicates that one entity characterizes, portrays, or refers to another entity’s death using a particular description, metaphor, or wording.
-
E.
deathBefore
Indicates that one entity’s death occurred earlier in time than another entity’s death.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf40f7908190a450c3136fccb020 |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41837e48190933572165be0ca38 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.