Triple
T10757005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chislehurst Caves |
E253721
|
entity |
| Predicate | areaServedAsShelterFor |
P95817
|
FINISHED |
| Object | thousands of people during World War II |
—
|
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: thousands of people during World War II | Statement: [Chislehurst Caves, areaServedAsShelterFor, thousands of people during World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaServedAsShelterFor Context triple: [Chislehurst Caves, areaServedAsShelterFor, thousands of people during World War II]
-
A.
hasShelters
Indicates that one entity provides, contains, or is associated with one or more shelters for another entity or purpose.
-
B.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
C.
shelterType
Indicates the kind or category of shelter associated with an entity (e.g., tent, house, bunker).
-
D.
hadSanctuaryOf
Indicates that an entity possessed or hosted a sanctuary dedicated to another entity.
-
E.
areaServedType
Indicates the type or category of area that is served by an entity or service.
- F. None of above. chosen
Provenance (4 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d72e9fded88190940df48344fc368e |
completed | April 9, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:15 p.m.