Triple
T2162314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fortified Sector of Thionville |
E46827
|
entity |
| Predicate | engagedInCombat |
P6697
|
FINISHED |
| Object | June 1940 |
—
|
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: June 1940 | Statement: [Fortified Sector of Thionville, engagedInCombat, June 1940]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagedInCombat Context triple: [Fortified Sector of Thionville, engagedInCombat, June 1940]
-
A.
battledIn
chosen
Indicates that two or more entities engaged in a battle or conflict that took place at a specific location or during a particular event.
-
B.
combatantsIncluded
Indicates that the specified entities are participants or parties involved in a particular combat or conflict.
-
C.
introducedToCombat
Indicates that something was brought into use or implemented specifically for the purpose of addressing or mitigating a particular problem, threat, or undesirable condition.
-
D.
mainCombatant
Indicates that the subject is the primary participant or leading party in a conflict, battle, or combat situation involving the object.
-
E.
numberLaunchedInCombat
Indicates the quantity of times an entity has been launched or deployed specifically in combat operations.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8b9c0881908373eabc7f81c394 |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9c90408190b6b65498ca43ce26 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.