Triple
T32926924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kunstberg |
E842296
|
entity |
| Predicate | hasPredecessorUse |
P203187
|
FINISHED |
| Object | densely built historic neighborhood |
—
|
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: densely built historic neighborhood | Statement: [Kunstberg, hasPredecessorUse, densely built historic neighborhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPredecessorUse Context triple: [Kunstberg, hasPredecessorUse, densely built historic neighborhood]
-
A.
hasSuccessorUse
Indicates that one use or application of something is directly followed or replaced by another use in a sequence or progression.
-
B.
predecessorUsedFrom
Indicates that something was used or derived from a preceding version, state, or entity that came before it.
-
C.
usedByPredecessorOf
Indicates that something is used by an entity that is the predecessor of another entity in a sequence or hierarchy.
-
D.
hasPredecessorType
Indicates that one type is derived from, follows, or is based on another earlier or more fundamental type in a sequence or hierarchy.
-
E.
hasPredecessorStructureFrom
Indicates that one structure existed or was established before another structure in a sequential or developmental order.
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0136e4af808190b529d324bbf0c5d9 |
completed | May 11, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_6a01369141c4819091cb8064913a44ca |
completed | May 11, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_6a0136e3d6ec8190898b5ab5a628a99d |
completed | May 11, 2026, 1:54 a.m. |
Created at: May 1, 2026, 1:20 a.m.