Triple
T33894984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elessar |
E868881
|
entity |
| Predicate | healsWith |
P84200
|
FINISHED |
| Object | Athelas |
—
|
NE NERFINISHED |
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: Athelas | Statement: [Elessar, healsWith, Athelas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healsWith Context triple: [Elessar, healsWith, Athelas]
-
A.
typeOfHealing
Indicates the specific method or modality by which a healing process is carried out or achieved.
-
B.
regeneratesHealthIn
Indicates that an entity’s health is restored or increased when it is within a specified context, area, or condition.
-
C.
hasRemedy
Indicates that one entity serves as a remedy, treatment, or corrective measure for a problem, condition, or undesirable state associated with another entity.
-
D.
receivesSupernaturalHealingFrom
Indicates that one entity is restored to health or cured through a supernatural or miraculous intervention provided by another entity.
-
E.
curedWith
chosen
Indicates that one entity is treated or healed by using another entity as the remedy or therapeutic method.
- 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_69f34996761c8190864e42f7c9cf215b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:48 a.m.