Triple
T32592205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twin Peaks, Washington |
E833100
|
entity |
| Predicate | hasFictionalPopulationType |
P49690
|
FINISHED |
| Object | logging community |
—
|
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: logging community | Statement: [Twin Peaks, Washington, hasFictionalPopulationType, logging community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPopulationType Context triple: [Twin Peaks, Washington, hasFictionalPopulationType, logging community]
-
A.
hasFictionalDemographic
Indicates that an entity is associated with a demographic group that is fictional or exists only within a created narrative or imagined context.
-
B.
fictionalPopulation
chosen
Indicates that a location or setting has an imagined or non-real population, as found in fictional works.
-
C.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
-
D.
hasFictionalTownType
Indicates that a fictional town is classified as being of a particular type or category.
-
E.
hasFictionalInhabitants
Indicates that a place or setting is inhabited by fictional or imaginary beings.
- 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_69f34929ff648190aded9424aa7564ae |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fedfd913f48190bdcd450980868d9a |
completed | May 9, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fedf58c6e88190821a7156054c9086 |
completed | May 9, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:05 a.m.