Triple
T25714804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Responder |
E644831
|
entity |
| Predicate | characterBasedIn |
P168038
|
FINISHED |
| Object | Liverpool |
—
|
NE NERFINISHED |
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: Liverpool | Statement: [The Responder, characterBasedIn, Liverpool]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterBasedIn Context triple: [The Responder, characterBasedIn, Liverpool]
-
A.
characterBasedOn
Indicates that one character is modeled, inspired, or derived from another real or fictional entity.
-
B.
basedOnCharacterBy
Indicates that one work, adaptation, or portrayal is derived from or inspired by a character created by another entity.
-
C.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
D.
basedOnCharacterOccupation
Indicates that something is derived from, inspired by, or determined according to a character’s occupation or job role.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 21, 2026, 9:38 p.m.