Triple
T4124999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorraine Motel |
E92702
|
entity |
| Predicate | closureAsMotel |
P12551
|
FINISHED |
| Object | 1980s |
—
|
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: 1980s | Statement: [Lorraine Motel, closureAsMotel, 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closureAsMotel Context triple: [Lorraine Motel, closureAsMotel, 1980s]
-
A.
closure
Indicates that an entity is closed or not accessible/available for use, entry, or interaction.
-
B.
closedDuring
chosen
Indicates that an entity is not open or available for use during a specified time period or under certain conditions.
-
C.
closureReason
Indicates the reason or cause for which an entity, process, or case has been closed or terminated.
-
D.
closingTheme
Indicates that one entity serves as the ending or closing theme (such as a song or musical piece) associated with another entity, typically a media work or episode.
-
E.
closingContains
Indicates that one closing element, event, or period fully includes another within its temporal or structural bounds.
- 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_69aed9685f70819086932777aec8d959 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:41 p.m.