Triple
T24962336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Passo Falzarego |
E624641
|
entity |
| Predicate | wasFrontLineBetween |
P84932
|
FINISHED |
| Object | Italy |
—
|
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: Italy | Statement: [Passo Falzarego, wasFrontLineBetween, Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasFrontLineBetween Context triple: [Passo Falzarego, wasFrontLineBetween, Italy]
-
A.
frontLineBetween
Indicates that a boundary or line of direct confrontation exists separating two opposing sides or regions.
-
B.
wasFrontierBetween
chosen
Indicates that one entity historically served as the boundary or border region separating two other entities.
-
C.
frontLineDuring
Indicates that an entity is positioned at or serves on the front line during a specified time or event.
-
D.
frontLine
Indicates that an entity is positioned at or associated with the foremost or primary line of engagement, activity, or defense relative to others.
-
E.
wasOnSideOf
Indicates that one entity supported, aligned with, or took the same side as another entity in a conflict, dispute, or opposing situation.
- 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_69e2ff23a3a88190b1b9743fe5e15f94 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f4242e3fd08190bc08e46222fb2c67 |
completed | May 1, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:59 a.m.