Triple
T10017761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cletus’ Chicken Shack |
E199537
|
entity |
| Predicate | hasCustomerBaseInFiction |
P91717
|
FINISHED |
| Object | residents of Springfield |
—
|
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: residents of Springfield | Statement: [Cletus’ Chicken Shack, hasCustomerBaseInFiction, residents of Springfield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomerBaseInFiction Context triple: [Cletus’ Chicken Shack, hasCustomerBaseInFiction, residents of Springfield]
-
A.
hasGroundsInFiction
Indicates that something is based on, justified by, or finds its origin within fictional works or narratives.
-
B.
hasChildInFiction
Indicates that a fictional work or character includes another character as their child within the fictional narrative.
-
C.
hasPlaceInFiction
Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
-
D.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
E.
hasFamilyNameInFiction
Indicates that a fictional character is associated with a particular family name within a work of fiction.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd4de1588190a89ed575cff0b8c9 |
completed | April 2, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69cd4b7cd4208190b2253583ee2f892c |
completed | April 1, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:53 p.m.