Triple
T8706888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WLM |
E206671
|
entity |
| Predicate | supportsGoalType |
P84655
|
FINISHED |
| Object | response time goals |
—
|
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: response time goals | Statement: [WLM, supportsGoalType, response time goals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsGoalType Context triple: [WLM, supportsGoalType, response time goals]
-
A.
supportGoal
Indicates that one entity actively helps, promotes, or contributes to the achievement of another entity’s goal.
-
B.
supportsPolicyGoal
Indicates that one entity’s actions, positions, or characteristics help advance, uphold, or contribute to achieving a specified policy goal.
-
C.
supportsType
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
D.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
-
E.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fe19ac8190936ba0faf513ed2b |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc582412f48190ae819965bfb0e75d |
completed | March 31, 2026, 11:26 p.m. |
Created at: March 30, 2026, 6:35 p.m.