Triple
T4084986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smallpox Hospital Ruins |
E87567
|
entity |
| Predicate | closedAsHospital |
P12551
|
FINISHED |
| Object | late 19th century |
—
|
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: late 19th century | Statement: [Smallpox Hospital Ruins, closedAsHospital, late 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closedAsHospital Context triple: [Smallpox Hospital Ruins, closedAsHospital, late 19th century]
-
A.
hasDischarge
Indicates that one entity releases, emits, or expels a substance, energy, or flow from itself.
-
B.
closedDuring
chosen
Indicates that an entity is not open or available for use during a specified time period or under certain conditions.
-
C.
closedAsPrison
Indicates that a facility or location was shut down specifically for use as a prison or place of incarceration.
-
D.
closedIn
Indicates that one entity is enclosed, contained, or surrounded within the boundaries or limits defined by another entity.
-
E.
containsHospital
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc7b7cc4819089cfbf2b1c23ccc5 |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.