Triple
T199570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panamanian golden frog |
E4071
|
entity |
| Predicate | defenseMechanism |
P1135
|
FINISHED |
| Object | poisonous skin secretions |
—
|
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: poisonous skin secretions | Statement: [Panamanian golden frog, defenseMechanism, poisonous skin secretions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defenseMechanism Context triple: [Panamanian golden frog, defenseMechanism, poisonous skin secretions]
-
A.
defenseResult
Indicates the outcome or consequence of a defensive action or strategy in response to an attack or threat.
-
B.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
-
C.
typeOfDefense
chosen
Indicates the specific kind or category of defense employed or possessed in a given context.
-
D.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
E.
securityMechanism
Indicates a relationship where one entity serves as a means or method to protect another entity from threats, vulnerabilities, or unauthorized actions.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.