Triple
T35974100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farhud |
E1040365
|
entity |
| Predicate | hasLootingExtent |
P199568
|
FINISHED |
| Object | widespread looting of Jewish homes and businesses |
—
|
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: widespread looting of Jewish homes and businesses | Statement: [Farhud, hasLootingExtent, widespread looting of Jewish homes and businesses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLootingExtent Context triple: [Farhud, hasLootingExtent, widespread looting of Jewish homes and businesses]
-
A.
canPickUpLoot
Indicates that one entity is able to collect or take possession of loot associated with another entity or location.
-
B.
lootRestriction
Indicates a rule or limitation on what loot can be obtained, used, or distributed in a given context.
-
C.
wasLooted
Indicates that an entity was forcibly taken or plundered, typically during a theft, raid, or act of violence.
-
D.
lootTableIncludes
Indicates that a particular loot table contains or can yield a specified item or reward.
-
E.
tieneAlcance
Indicates that something possesses or has a certain scope, reach, or range of effect in relation to something else.
- 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_69f76e27758c81909b711cf38a130aaf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff45793d5c81909dc503ad1f714ee2 |
completed | May 9, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69ff41cb0e088190a6e9b03cb20e5fad |
completed | May 9, 2026, 2:16 p.m. |
| PDg | Predicate description generation | batch_69ff45782cb88190b604811e4d724382 |
completed | May 9, 2026, 2:32 p.m. |
Created at: May 3, 2026, 4:07 p.m.