Triple
T5420828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam-I-Am |
E121243
|
entity |
| Predicate | persuades |
P836
|
FINISHED |
| Object | the unnamed protagonist in Green Eggs and Ham |
—
|
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: the unnamed protagonist in Green Eggs and Ham | Statement: [Sam-I-Am, persuades, the unnamed protagonist in Green Eggs and Ham]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: persuades Context triple: [Sam-I-Am, persuades, the unnamed protagonist in Green Eggs and Ham]
-
A.
promotes
Indicates that one entity actively supports, advances, or encourages the growth, adoption, or success of another entity or outcome.
-
B.
proposes
Indicates that one entity formally suggests or puts forward an idea, plan, or course of action to another entity for consideration or approval.
-
C.
advises
Indicates that one entity provides guidance, recommendations, or counsel to another entity.
-
D.
encourages
chosen
Indicates actively motivating, supporting, or giving confidence to another entity to pursue an action, behavior, or state.
-
E.
discourages
Indicates an action or influence that deters, dissuades, or reduces the likelihood of someone performing a particular behavior or pursuing a certain outcome.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87eac41481908a4982db5d119edd |
completed | March 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.