Triple
T37969383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Jemgum |
E947236
|
entity |
| Predicate | involvesMilitaryForce |
P39448
|
FINISHED |
| Object | Spanish Army of Flanders |
—
|
NE NERFINISHED |
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: Spanish Army of Flanders | Statement: [Battle of Jemgum, involvesMilitaryForce, Spanish Army of Flanders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesMilitaryForce Context triple: [Battle of Jemgum, involvesMilitaryForce, Spanish Army of Flanders]
-
A.
involvedForeignTroops
Indicates that the event or situation included the participation or presence of military forces from a foreign country.
-
B.
armedForcesInvolved
chosen
Indicates that the relationship or event involves the participation or presence of military or armed forces.
-
C.
militaryForceUsed
Indicates that one entity employs or applies military power or armed force against, within, or in relation to another entity or situation.
-
D.
involvedForcesType
Indicates the type or category of forces that participate in or are associated with a given event, interaction, or situation.
-
E.
numberOfTroopsInvolved
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
- 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_69f76ef7db908190bba6086673a32300 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fecb4d02f881909a9ee97ce98000d5 |
completed | May 9, 2026, 5:51 a.m. |
| PD | Predicate disambiguation | batch_69fec9846c1c8190b317f0711f0755db |
completed | May 9, 2026, 5:43 a.m. |
Created at: May 3, 2026, 4:20 p.m.