Triple
T37460968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yogg-Saron, Hope’s End |
E930914
|
entity |
| Predicate | targetingBehavior |
P199357
|
FINISHED |
| Object | Targets chosen randomly |
—
|
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: Targets chosen randomly | Statement: [Yogg-Saron, Hope’s End, targetingBehavior, Targets chosen randomly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetingBehavior Context triple: [Yogg-Saron, Hope’s End, targetingBehavior, Targets chosen randomly]
-
A.
targetingRule
chosen
Indicates a rule that defines which entities are selected or targeted based on specified conditions or criteria.
-
B.
targetBehaviorChange
Indicates a relationship where an intervention or influence is intended to alter, modify, or redirect an entity’s behavior from its current state to a desired new state.
-
C.
targetedBecauseOf
Indicates that one entity is made a target of an action, harm, or scrutiny specifically due to possessing a particular attribute, identity, or characteristic.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
targetedPolicy
Indicates that a policy is specifically directed at, or designed to affect, a particular subset of entities rather than applying broadly.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff32b88bf48190b45afd1b60cb511c |
completed | May 9, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69ff3031e18881908927b2ab452de863 |
completed | May 9, 2026, 1:01 p.m. |
Created at: May 3, 2026, 4:17 p.m.