Triple
T33478187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Collins’s proposal to Elizabeth Bennet |
E857382
|
entity |
| Predicate | includesDetail |
P1393
|
FINISHED |
| Object | Mr. Collins lists practical advantages of the match |
—
|
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: Mr. Collins lists practical advantages of the match | Statement: [Mr. Collins’s proposal to Elizabeth Bennet, includesDetail, Mr. Collins lists practical advantages of the match]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesDetail Context triple: [Mr. Collins’s proposal to Elizabeth Bennet, includesDetail, Mr. Collins lists practical advantages of the match]
-
A.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
-
B.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
C.
includesResponse
Indicates that one entity contains, incorporates, or encompasses another entity as a response or reply.
-
D.
includedSingle
Indicates that one specific, individual item is contained within or made part of another set, group, or collection.
-
E.
includesSee
Indicates that one entity’s scope, content, or experience contains or encompasses the act of seeing or visual perception involving another entity.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0324c2d618819093f7e6424b0f5baf |
completed | May 12, 2026, 1:01 p.m. |
| PD | Predicate disambiguation | batch_6a0324292e588190b37d0c3016ea2062 |
completed | May 12, 2026, 12:59 p.m. |
Created at: May 1, 2026, 1:38 a.m.