Triple
T24916034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Courthouse station |
E623985
|
entity |
| Predicate | sheltersFromWeather |
P77310
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Courthouse station, sheltersFromWeather, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sheltersFromWeather Context triple: [Courthouse station, sheltersFromWeather, yes]
-
A.
relativeShelterFrom
Indicates that one entity provides shelter or protection for another entity relative to some reference condition, location, or alternative.
-
B.
shelterType
Indicates the kind or category of shelter associated with an entity (e.g., tent, house, bunker).
-
C.
hasShelters
Indicates that one entity provides, contains, or is associated with one or more shelters for another entity or purpose.
-
D.
areaServedAsShelterFor
Indicates that one entity functioned as a shelter or refuge for another entity, providing protection or a safe place.
-
E.
sheltersPeopleFleeing
chosen
Indicates that an entity provides refuge or protection to people who are escaping danger, persecution, or adverse conditions.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f4238c52488190a58b1191f4dc3373 |
completed | May 1, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:28 a.m.