Triple
T21306427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Springwood, Ohio |
E525209
|
entity |
| Predicate | hasFictionalPopulation |
P49690
|
FINISHED |
| Object | families of Elm Street children |
—
|
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: families of Elm Street children | Statement: [Springwood, Ohio, hasFictionalPopulation, families of Elm Street children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPopulation Context triple: [Springwood, Ohio, hasFictionalPopulation, families of Elm Street children]
-
A.
fictionalPopulation
chosen
Indicates that a location or setting has an imagined or non-real population, as found in fictional works.
-
B.
hasFictionalDemographic
Indicates that an entity is associated with a demographic group that is fictional or exists only within a created narrative or imagined context.
-
C.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
D.
hasFictionalInhabitants
Indicates that a place or setting is inhabited by fictional or imaginary beings.
-
E.
hasFictionalTownBasedOn
Indicates that a fictional town is modeled on, inspired by, or derived from a specific real-world town or 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75aa52a508190bb5dc806b6483574 |
completed | April 21, 2026, 11:08 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:05 p.m.