Triple
T19165004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zerbst |
E469155
|
entity |
| Predicate | percentageDestroyedInWWII |
P10453
|
FINISHED |
| Object | about 80 percent of the town centre |
—
|
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: about 80 percent of the town centre | Statement: [Zerbst, percentageDestroyedInWWII, about 80 percent of the town centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageDestroyedInWWII Context triple: [Zerbst, percentageDestroyedInWWII, about 80 percent of the town centre]
-
A.
percentageDestroyedInWWIIApproximate
chosen
Indicates the approximate proportion of something that was destroyed during World War II.
-
B.
numberOfHoldersKilledInWorldWarII
Indicates the number of holders of a given title, position, or role who were killed during World War II.
-
C.
statusDuringWorldWarII
Indicates the role, condition, or classification an entity had specifically during the period of World War II.
-
D.
sideInWorldWarII
Indicates that an entity was aligned with or participated on a particular side during World War II.
-
E.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f15e2720819084b1707497db26a2 |
completed | April 20, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.