Triple
T27782847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hill Valley Library |
E699378
|
entity |
| Predicate | partOfFictionalMunicipality |
P14483
|
FINISHED |
| Object | Hill Valley town center |
—
|
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: Hill Valley town center | Statement: [Hill Valley Library, partOfFictionalMunicipality, Hill Valley town center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfFictionalMunicipality Context triple: [Hill Valley Library, partOfFictionalMunicipality, Hill Valley town center]
-
A.
partOfFictionalCity
chosen
Indicates that one entity is a component, area, or subdivision within a larger fictional city.
-
B.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or location.
-
C.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
D.
hasFictionalNearbyTown
Indicates that an entity is associated with a fictional town located in its vicinity or surrounding area.
-
E.
boroughOfFictionalSetting
Indicates that a fictional setting is located within or associated with a specific borough.
- 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_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: April 27, 2026, 5:11 p.m.