Triple
T29908529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bommersheim |
E759605
|
entity |
| Predicate | hasLocalHistoricalRoots |
P190492
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bommersheim, hasLocalHistoricalRoots, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalHistoricalRoots Context triple: [Bommersheim, hasLocalHistoricalRoots, true]
-
A.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
B.
hasAncestralRoots
Indicates that one entity originates from, descends from, or is historically rooted in another entity or place.
-
C.
hasLocalGovernmentHistory
Indicates that an entity has a documented history or record of its local governmental structure, activities, or developments.
-
D.
hasHistoricalSubstratum
Indicates that one entity is historically underlain or influenced by another, earlier cultural, linguistic, or structural layer.
-
E.
hasHistoricalOriginInYear
Indicates that something first originated, began, or came into existence in a specified calendar year.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fcc7779d248190afdb348a95375443 |
completed | May 7, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
| PDg | Predicate description generation | batch_69fcc73264e08190b0b5917f32226fae |
completed | May 7, 2026, 5:09 p.m. |
Created at: April 29, 2026, 6:09 p.m.