Triple
T3658118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergen op Zoom |
E77581
|
entity |
| Predicate | hasFortificationType |
P30468
|
FINISHED |
| Object | star fort elements |
—
|
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: star fort elements | Statement: [Bergen op Zoom, hasFortificationType, star fort elements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFortificationType Context triple: [Bergen op Zoom, hasFortificationType, star fort elements]
-
A.
hasFortifications
Indicates that one entity possesses or is equipped with defensive structures or fortification works associated with it.
-
B.
isFortifiedCity
Indicates that a city is strengthened with defensive structures or fortifications, such as walls, ramparts, or similar protective works.
-
C.
containsFortress
Indicates that a location or area includes a fortress within its boundaries.
-
D.
wasFortifiedBy
Indicates that a place or structure received defensive strengthening or fortification through the actions or resources of a specified agent or entity.
-
E.
fortType
chosen
Indicates the specific kind or classification of a fort associated with an entity.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d48a2081908ac0f76d548a53ee |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.