Triple
T2703862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Generative Adversarial Networks |
E59296
|
entity |
| Predicate | discriminatorGoal |
P32840
|
FINISHED |
| Object | distinguish real from fake samples |
—
|
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: distinguish real from fake samples | Statement: [Generative Adversarial Networks, discriminatorGoal, distinguish real from fake samples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discriminatorGoal Context triple: [Generative Adversarial Networks, discriminatorGoal, distinguish real from fake samples]
-
A.
statedAsGoalFor
chosen
Indicates that something has been explicitly declared or identified as a goal for a particular entity or context.
-
B.
laterGoal
Indicates that one goal occurs or is intended to be achieved after another goal in time.
-
C.
secondaryGoal
Indicates that something serves as a subordinate or supporting objective in addition to a primary goal.
-
D.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
E.
legacyGoal
Indicates that an entity has a long-term, enduring objective or impact it aims to leave behind beyond its immediate actions or existence.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda5011bc8190ae4e41da391e759c |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.