Triple
T27782682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cafe 80's |
E699374
|
entity |
| Predicate | streetLocationInFiction |
P129229
|
FINISHED |
| Object | Courthouse Square, Hill Valley |
—
|
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: Courthouse Square, Hill Valley | Statement: [Cafe 80's, streetLocationInFiction, Courthouse Square, Hill Valley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetLocationInFiction Context triple: [Cafe 80's, streetLocationInFiction, Courthouse Square, Hill Valley]
-
A.
locatedOnFictionalRoute
Indicates that something is situated along or associated with a route that exists only within a fictional or imaginary setting.
-
B.
streetLocation
Indicates that one entity is located on, along, or at a specific street associated with the other entity.
-
C.
fictionalStreetSetting
chosen
Indicates that an entity is set on or associated with a street that exists only within a fictional or imaginary context.
-
D.
basedInFictionalWorkLocation
Indicates that an entity’s location or setting is situated within a fictional place as depicted in a specific creative work.
-
E.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
- 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6895f0819088655277e45859a8 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 5:11 p.m.