Triple
T19875677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanon and Israel |
E477628
|
entity |
| Predicate | statusOfWar |
P88699
|
FINISHED |
| Object | technically at war |
—
|
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: technically at war | Statement: [Lebanon and Israel, statusOfWar, technically at war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusOfWar Context triple: [Lebanon and Israel, statusOfWar, technically at war]
-
A.
warStatus
chosen
Indicates the state or condition of conflict or war that exists between entities at a given time.
-
B.
countryAtWarWith
Indicates that two countries are engaged in an active state of war or armed conflict with each other.
-
C.
statusDuringWar
Indicates the role, condition, or classification an entity held specifically during a period of war.
-
D.
warName
Indicates the specific name or title assigned to a particular war or armed conflict.
-
E.
legalStatusAfterWar
Indicates the legal condition or classification assigned to an entity as a consequence of, or following the conclusion of, a war or armed conflict.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658db058c8190b7bf0b003ead5bfc |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.