Triple
T19075885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meroz |
E466900
|
entity |
| Predicate | reasonForCurse |
P134237
|
FINISHED |
| Object | failed to come to the help of the LORD |
—
|
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: failed to come to the help of the LORD | Statement: [Meroz, reasonForCurse, failed to come to the help of the LORD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForCurse Context triple: [Meroz, reasonForCurse, failed to come to the help of the LORD]
-
A.
timeOfCurse
Indicates the specific time at which a curse is cast, activated, or takes effect in relation to an entity or event.
-
B.
curseCondition
Indicates a condition or state in which an entity is affected by a curse or cursed effect.
-
C.
associatedCurse
Indicates that one entity is linked to, affected by, or bears responsibility for a particular curse related to another entity.
-
D.
scripturalCurse
Indicates that one entity pronounces or embodies a curse upon another as recorded or prescribed in a religious or scriptural context.
-
E.
reasonForBan
Indicates the justification or cause that led to an entity being banned.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e49c7c8190b6ce7b918086b23c |
completed | April 20, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:04 p.m.