Triple
T28929860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augers |
E733749
|
entity |
| Predicate | enemyBehavior |
P166029
|
FINISHED |
| Object | enter house through windows and doors |
—
|
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: enter house through windows and doors | Statement: [Augers, enemyBehavior, enter house through windows and doors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enemyBehavior Context triple: [Augers, enemyBehavior, enter house through windows and doors]
-
A.
enemyState
Indicates a relationship where one state is hostile or in opposition to another state, typically involving conflict, rivalry, or adversarial intentions.
-
B.
behaviorNear
Indicates that one entity exhibits a behavior or action in close spatial proximity to another entity.
-
C.
enemyType
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
D.
aiBehavior
Indicates how an artificial intelligence system acts or responds under given conditions or stimuli.
-
E.
behaviorCode
Indicates the specific rule, standard, or classification code that governs or characterizes an entity’s behavior in a given context.
- 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_69f05b0b49b08190b8994b339c7980f6 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65bb75cd08190bbdb63c093ad6210 |
completed | May 2, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65b136b30819090cf59fb772f35f1 |
completed | May 2, 2026, 8:14 p.m. |
Created at: April 28, 2026, 8:27 a.m.