Triple
T1000773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Bowls |
E21596
|
entity |
| Predicate | thirdBowlEffect |
P22299
|
FINISHED |
| Object | rivers and springs turned to blood |
—
|
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: rivers and springs turned to blood | Statement: [Seven Bowls, thirdBowlEffect, rivers and springs turned to blood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdBowlEffect Context triple: [Seven Bowls, thirdBowlEffect, rivers and springs turned to blood]
-
A.
includesBowl
Indicates that something contains or has a bowl as one of its components or elements.
-
B.
thirdPlacePrize
Indicates that an entity receives or is associated with the prize awarded for finishing in third place in a competition or ranking.
-
C.
thirdTier
Indicates that an entity occupies a third level or rank within a hierarchical structure or classification.
-
D.
bowlAccess
Indicates that one entity has the ability or permission to access or use a particular bowl.
-
E.
thirdPlacePlayoff
Indicates a match or contest held to determine which participant finishes in third place, typically between the losers of the semifinals.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b057c48190b9e42df9246b3757 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b3a02ea481909555cf5b7bed0d9a |
completed | March 1, 2026, 9:46 p.m. |
Created at: March 1, 2026, 7:41 p.m.