Triple
T30198395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Cyzicus |
E767696
|
entity |
| Predicate | hasSiegeType |
P75812
|
FINISHED |
| Object | land siege |
—
|
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: land siege | Statement: [Siege of Cyzicus, hasSiegeType, land siege]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSiegeType Context triple: [Siege of Cyzicus, hasSiegeType, land siege]
-
A.
typeOfSiege
chosen
Indicates the specific kind or category of siege involved in a conflict or military operation.
-
B.
isSiegeOf
Indicates a relationship where one event or action constitutes the military siege of a particular place, target, or entity.
-
C.
siegeRelated
Indicates a relationship in which one entity is involved with, associated with, or relevant to a siege or siege-related activities.
-
D.
hasMajorSiege
Indicates that a significant or large-scale siege event occurred involving the related entities.
-
E.
opposedSiegeBy
Indicates that one party actively resisted, countered, or worked against another party’s siege.
- 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: April 29, 2026, 7:30 p.m.