Triple
T3054246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łódź Ghetto |
E60440
|
entity |
| Predicate | victimCountApproximate |
P1785
|
FINISHED |
| Object | over 100000 murdered |
—
|
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 100000 murdered | Statement: [Łódź Ghetto, victimCountApproximate, over 100000 murdered]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimCountApproximate Context triple: [Łódź Ghetto, victimCountApproximate, over 100000 murdered]
-
A.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
B.
mainVictims
Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
-
C.
deathToll
chosen
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
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.
estimatedMurdersCommitted
Indicates an approximate count of murders that are believed or inferred to have been committed by an entity.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf51b5081908ce355a76cfa9e3c |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.