Triple
T37460537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loatheb |
E930904
|
entity |
| Predicate | effectMagnitude |
P1937
|
FINISHED |
| Object | +5 mana cost to enemy spells |
—
|
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: +5 mana cost to enemy spells | Statement: [Loatheb, effectMagnitude, +5 mana cost to enemy spells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectMagnitude Context triple: [Loatheb, effectMagnitude, +5 mana cost to enemy spells]
-
A.
magnitude
chosen
Indicates a relationship where a quantitative size, extent, or intensity is assigned to or compared between entities or values.
-
B.
measuredEffect
Indicates that an action or process has produced a specific, quantified outcome or impact on something.
-
C.
exampleMagnitude
Indicates a relationship where one entity serves as a representative or typical instance that illustrates the scale, size, or intensity (magnitude) of another entity or quantity.
-
D.
effectEmphasis
Indicates that one entity highlights, intensifies, or draws special attention to the effect produced by another entity or action.
-
E.
magnitudeScale
Indicates the scale or measurement system used to quantify the magnitude or intensity of something.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fdec5ffe088190ac5505f26c6cff18 |
completed | May 8, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69fdeae15f1c81908fc63fbc1b028d2e |
completed | May 8, 2026, 1:53 p.m. |
Created at: May 3, 2026, 4:17 p.m.