Triple
T4347002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern France campaign |
E97928
|
entity |
| Predicate | includedLanding |
P1393
|
FINISHED |
| Object | landings in Provence |
—
|
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: landings in Provence | Statement: [Southern France campaign, includedLanding, landings in Provence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedLanding Context triple: [Southern France campaign, includedLanding, landings in Provence]
-
A.
landing
Indicates the action or event of an entity coming down from the air or a higher position to make controlled contact with a surface.
-
B.
landingArea
Indicates that a location or surface serves as a designated area where something (such as an aircraft, object, or person) can land.
-
C.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
D.
hasLandingConditions
Indicates the specific conditions or requirements that must be met for a landing to occur or be permitted.
-
E.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3518d6728819084a2f40ae0bd3ac8 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:15 p.m.