Triple
T33899539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Ireland |
E869008
|
entity |
| Predicate | notableGroupDeaths |
P19083
|
FINISHED |
| Object | over 150 Salvation Army members |
—
|
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 150 Salvation Army members | Statement: [SS Empress of Ireland, notableGroupDeaths, over 150 Salvation Army members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGroupDeaths Context triple: [SS Empress of Ireland, notableGroupDeaths, over 150 Salvation Army members]
-
A.
notableVictims
chosen
Indicates that the object is a person or group who is especially well-known or significant as a victim of the subject.
-
B.
notableDeathTollEvent
Indicates that an event is characterized by causing an unusually large or historically significant number of deaths.
-
C.
numberOfDeathsInNotableEvent
Indicates the total count of deaths that occurred as a result of a specified notable event.
-
D.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
E.
militaryDeaths
Indicates the number of individuals who died while serving in a military capacity, typically during armed conflict or related operations.
- 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_69f34997703c8190866b1d404bce531f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:48 a.m.