Triple
T14859758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bock Casemates |
E349456
|
entity |
| Predicate | capacityShelter |
P38868
|
FINISHED |
| Object | thousands of people |
—
|
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 | Statement: [Bock Casemates, capacityShelter, thousands of people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityShelter Context triple: [Bock Casemates, capacityShelter, thousands of people]
-
A.
roomCapacity
Indicates the maximum number of people or occupants that a room is designed or allowed to hold.
-
B.
areaServedAsShelterFor
Indicates that one entity functioned as a shelter or refuge for another entity, providing protection or a safe place.
-
C.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
D.
capacityCategory
chosen
Indicates the classification of something based on the amount or volume it can hold, handle, or accommodate.
-
E.
shelterType
Indicates the kind or category of shelter associated with an entity (e.g., tent, house, bunker).
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44598e48190b759a05ed2d9ecaf |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.