Triple
T25631237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luisenstadt |
E642581
|
entity |
| Predicate | partlyDividedBy |
P69233
|
FINISHED |
| Object | Berlin Wall |
—
|
NE NERFINISHED |
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: Berlin Wall | Statement: [Luisenstadt, partlyDividedBy, Berlin Wall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partlyDividedBy Context triple: [Luisenstadt, partlyDividedBy, Berlin Wall]
-
A.
dividedBy
Indicates that one quantity is separated into a specified number of equal parts or groups by another quantity, representing a division relationship between them.
-
B.
isDividedFrom
chosen
Indicates that one entity is separated or partitioned from another, typically by a boundary, barrier, or dividing line.
-
C.
sometimesDividedInto
Indicates that an entity is on some occasions partitioned or separated into distinct parts, sections, or groups, but not always.
-
D.
dividedIn
Indicates that one entity is partitioned or separated into multiple distinct parts, sections, or groups represented by another entity.
-
E.
dividedBetween
Indicates that something is partitioned or shared among two or more distinct entities or groups.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa5dd31481909bfcbb9975403cc5 |
completed | May 2, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 5:18 p.m.