Triple
T30876252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anti-Nephi-Lehies |
E786481
|
entity |
| Predicate | effectOnEnemies |
P58916
|
FINISHED |
| Object | led many attacking Lamanites to feel remorse |
—
|
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: led many attacking Lamanites to feel remorse | Statement: [Anti-Nephi-Lehies, effectOnEnemies, led many attacking Lamanites to feel remorse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnEnemies Context triple: [Anti-Nephi-Lehies, effectOnEnemies, led many attacking Lamanites to feel remorse]
-
A.
attackEffect
Indicates that one entity’s attack produces a specific effect or consequence on another entity.
-
B.
effectOnOthers
chosen
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
C.
effectivenessAgainst
Indicates how well one entity performs in countering, influencing, or mitigating the impact of another entity.
-
D.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
E.
defeatEffect
Indicates that one entity’s defeat causes a particular outcome or change to occur for another entity or the overall situation.
- 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: April 29, 2026, 8:48 p.m.