Triple
T29341005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Executor |
E744035
|
entity |
| Predicate | featuresObjectiveType |
P72446
|
FINISHED |
| Object | infiltration |
—
|
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: infiltration | Statement: [The Executor, featuresObjectiveType, infiltration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresObjectiveType Context triple: [The Executor, featuresObjectiveType, infiltration]
-
A.
goalType
chosen
Indicates the specific category or nature of a goal associated with an entity or action.
-
B.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
C.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
D.
usesObjective
Indicates that an agent employs or applies a particular object, tool, or resource to carry out an action or achieve a goal.
-
E.
featureTypeCatalog
Indicates that an entity is associated with, or defined by, a catalog that specifies the types of features it can include or reference.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69ff63225b6481909217ad11b4f7d3ba |
completed | May 9, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69ff60e0882c819085d097010db43ee0 |
completed | May 9, 2026, 4:29 p.m. |
Created at: April 28, 2026, 1:33 p.m.