Triple
T36555254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arda Marred |
E901681
|
entity |
| Predicate | toBeHealedIn |
P185848
|
FINISHED |
| Object | Arda Healed |
—
|
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: Arda Healed | Statement: [Arda Marred, toBeHealedIn, Arda Healed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toBeHealedIn Context triple: [Arda Marred, toBeHealedIn, Arda Healed]
-
A.
recoveryDuration
Indicates the length of time required for an entity to return to a normal or functional state after an event, condition, or disruption.
-
B.
repairedInTimeFor
Indicates that something was successfully repaired before a relevant deadline or needed time.
-
C.
regeneratesHealthIn
Indicates that an entity’s health is restored or increased when it is within a specified context, area, or condition.
-
D.
regeneratesIn
Indicates that an entity restores or regrows itself within, or as a result of conditions in, a specified environment, context, or time period.
-
E.
curedWith
Indicates that one entity is treated or healed by using another entity as the remedy or therapeutic method.
- 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_69f76e634e9481908c9ba1b87ab87c26 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c3705b5c81908c84004543a71c07 |
completed | May 3, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:11 p.m.