Triple
T3421980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | relief of Rouen (1592) |
E72133
|
entity |
| Predicate | opposedSiegeBy |
P48622
|
FINISHED |
| Object | Protestant and royalist besieging army |
—
|
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: Protestant and royalist besieging army | Statement: [relief of Rouen (1592), opposedSiegeBy, Protestant and royalist besieging army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedSiegeBy Context triple: [relief of Rouen (1592), opposedSiegeBy, Protestant and royalist besieging army]
-
A.
isSiegeOf
Indicates a relationship where one event or action constitutes the military siege of a particular place, target, or entity.
-
B.
besiegedIn
Indicates that one entity is under siege at, or during the event of, another specified location or time.
-
C.
opposedWar
Indicates that an entity actively resisted, disagreed with, or worked against a particular war or military conflict.
-
D.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
-
E.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
- 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_69ad85ad38e48190b7660c5118a35289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb950f65481908c4aad15516e7a7c |
completed | March 8, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69adadfea024819094b41a13bc004bda |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb00f4f8c81908f88daf71f6a9c29 |
completed | March 8, 2026, 5:21 p.m. |
Created at: March 8, 2026, 3:15 p.m.