Triple
T1000772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Bowls |
E21596
|
entity |
| Predicate | secondBowlEffect |
P22298
|
FINISHED |
| Object | sea 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: sea turned to blood | Statement: [Seven Bowls, secondBowlEffect, sea turned to blood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondBowlEffect Context triple: [Seven Bowls, secondBowlEffect, sea turned to blood]
-
A.
secondPhase
Indicates that an entity is in, or has progressed to, the second phase or stage of a multi-phase process or sequence.
-
B.
secondTier
Indicates that something occupies a secondary or subordinate level of importance, quality, or rank relative to a primary or top tier.
-
C.
secondTemptation
Indicates a relationship where an entity is subjected to or engages in a second instance of temptation, following an initial tempting event.
-
D.
secondLetter
Indicates that one entity is the second letter (in sequence or position) of another entity, typically a string or word.
-
E.
secondOnlyTo
Indicates that one entity ranks immediately below another in degree, importance, or quality, with only that other entity surpassing it.
- 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.