Triple
T34084779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPAM (canned meat) |
E874149
|
entity |
| Predicate | reasonForInspiredTerm |
P95447
|
FINISHED |
| Object | overabundance and repetition association |
—
|
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: overabundance and repetition association | Statement: [SPAM (canned meat), reasonForInspiredTerm, overabundance and repetition association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForInspiredTerm Context triple: [SPAM (canned meat), reasonForInspiredTerm, overabundance and repetition association]
-
A.
inspiredTermMeaning
chosen
Indicates that one term’s meaning is derived from, modeled after, or conceptually influenced by another term.
-
B.
reasonForName
Indicates the explanation or cause behind why an entity has a particular name.
-
C.
etymologyReason
Indicates the reason, source, or origin explaining how or why a term acquired its particular etymology.
-
D.
reasonForEpithet
Indicates the cause, motivation, or circumstance that explains why a particular epithet is applied to an entity.
-
E.
conceptCoinedFromName
Indicates that a concept was created or derived from a specific person's name.
- 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_69f349a61d448190b74642f325d3eb7a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 1, 2026, 1:52 a.m.