Triple
T4117846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Morris |
E90336
|
entity |
| Predicate | basedOnRealPersonFor |
P54368
|
FINISHED |
| Object | character in "Escape from Alcatraz" |
—
|
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: character in "Escape from Alcatraz" | Statement: [Frank Morris, basedOnRealPersonFor, character in "Escape from Alcatraz"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnRealPersonFor Context triple: [Frank Morris, basedOnRealPersonFor, character in "Escape from Alcatraz"]
-
A.
basedOnRealRegion
Indicates that something is derived from, inspired by, or corresponds to an actual geographic or administrative region in the real world.
-
B.
hasFrontPerson
Indicates that an entity is represented, led, or fronted publicly by a specific person.
-
C.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
-
D.
testedPerson
Indicates that one entity has been subjected to a test, examination, or evaluation involving another entity.
-
E.
isHuman
Indicates that the subject entity possesses the defining characteristics or status of being a human.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af0245adbc81908b89a40850047975 |
completed | March 9, 2026, 5:24 p.m. |
Created at: March 9, 2026, 3:41 p.m.