Triple
T29068149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chencho Corleone |
E735741
|
entity |
| Predicate | positionInDuo |
P193712
|
FINISHED |
| Object | one half of Plan B |
—
|
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: one half of Plan B | Statement: [Chencho Corleone, positionInDuo, one half of Plan B]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInDuo Context triple: [Chencho Corleone, positionInDuo, one half of Plan B]
-
A.
positionInTrio
Indicates the specific ordered place an entity occupies within a three-member group or trio.
-
B.
positionInCase
Indicates the specific role, status, or placement that an entity holds within a particular case or legal proceeding.
-
C.
positionB
Indicates that one entity occupies or is located at a specific position relative to another entity.
-
D.
positionA
Indicates the spatial or ordered position of an entity A within a defined reference frame or sequence.
-
E.
positionOften
Indicates that one entity frequently holds, occupies, or is located at a particular position relative to another entity or context.
- 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fd509cdc5c8190a5f2c451bc0d0b25 |
completed | May 8, 2026, 2:55 a.m. |
Created at: April 28, 2026, 10:19 a.m.