Triple
T20133929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Lerna |
E490969
|
entity |
| Predicate | hydraRegeneration |
P48091
|
FINISHED |
| Object | heads regrew when cut off |
—
|
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: heads regrew when cut off | Statement: [Lake Lerna, hydraRegeneration, heads regrew when cut off]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hydraRegeneration Context triple: [Lake Lerna, hydraRegeneration, heads regrew when cut off]
-
A.
regeneratesHealthIn
Indicates that an entity’s health is restored or increased when it is within a specified context, area, or condition.
-
B.
regenerationAbility
chosen
Indicates the capability of an entity to restore or regrow lost or damaged parts of itself.
-
C.
regeneratesIn
Indicates that an entity restores or regrows itself within, or as a result of conditions in, a specified environment, context, or time period.
-
D.
methodOfRejuvenation
Indicates a process or technique used to restore youthfulness, vitality, or an earlier optimal state to something or someone.
-
E.
revivesSpiritOf
Indicates restoring or reawakening the emotional, cultural, or motivational essence associated with someone or 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6676556c481909ffc80cd2009b65a |
completed | April 20, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:32 p.m.