Triple
T10815878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prison Ship Martyrs’ Monument |
E255225
|
entity |
| Predicate | numberOfInterred |
P95901
|
FINISHED |
| Object | over 11,500 remains |
—
|
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: over 11,500 remains | Statement: [Prison Ship Martyrs’ Monument, numberOfInterred, over 11,500 remains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInterred Context triple: [Prison Ship Martyrs’ Monument, numberOfInterred, over 11,500 remains]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
numberOfUnidentifiedBurials
Indicates the count of burial sites or graves where the interred individuals have not been identified.
-
C.
numberOfCoffins
Indicates the quantity of coffins associated with a given entity or situation.
-
D.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
-
E.
hasBurialsOf
Indicates that a location or site contains or includes the burial places of certain individuals or groups.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733edab248190b2cf7f7bc2684468 |
completed | April 9, 2026, 5:06 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:18 p.m.