Triple
T17991587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milseburg |
E430385
|
entity |
| Predicate | hasHistoricalRemains |
P115122
|
FINISHED |
| Object | ramparts |
—
|
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: ramparts | Statement: [Milseburg, hasHistoricalRemains, ramparts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalRemains Context triple: [Milseburg, hasHistoricalRemains, ramparts]
-
A.
hasHistoricSite
Indicates that an entity possesses, contains, or is associated with a place recognized for its historical significance.
-
B.
hasArchaeologicalRemainsFromPeriod
Indicates that an entity contains or preserves archaeological remains originating from a specified historical period.
-
C.
hasRomanRemains
chosen
Indicates that the subject contains or is the location of physical remains or archaeological evidence from the Roman period.
-
D.
historicalExistence
Indicates that an entity actually existed at some point in real-world history, as opposed to being fictional, hypothetical, or mythological.
-
E.
hasArchaeologicalSiteIn
Indicates that an entity possesses, contains, or is associated with an archaeological site located within a specified place or region.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29fd7648190b7f09ea60c7b96a8 |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.