Triple
T3864165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obetia |
E91808
|
entity |
| Predicate | hasDefenseMechanism |
P1135
|
FINISHED |
| Object | chemical irritants in hairs |
—
|
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: chemical irritants in hairs | Statement: [Obetia, hasDefenseMechanism, chemical irritants in hairs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDefenseMechanism Context triple: [Obetia, hasDefenseMechanism, chemical irritants in hairs]
-
A.
hasMechanism
Indicates that one entity operates, functions, or produces an effect through the specified mechanism or process.
-
B.
canBeDefendedIn
Indicates that something (such as a claim, action, or position) is capable of being justified or supported within a specified context, forum, or framework.
-
C.
hasWeakness
Indicates that one entity is vulnerable to, or can be adversely affected or defeated by, another entity.
-
D.
typeOfDefense
chosen
Indicates the specific kind or category of defense employed or possessed in a given context.
-
E.
hasDefenderStrength
Indicates that an entity possesses a certain level or measure of defensive capability or protective power.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3871d881909c6c8e6d08203801 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.