Triple
T27214210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Beirut |
E684090
|
entity |
| Predicate | politicalOrientationDuringWar |
P88905
|
FINISHED |
| Object | largely pro-Palestinian |
—
|
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: largely pro-Palestinian | Statement: [West Beirut, politicalOrientationDuringWar, largely pro-Palestinian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalOrientationDuringWar Context triple: [West Beirut, politicalOrientationDuringWar, largely pro-Palestinian]
-
A.
countryDuringWar
Indicates that a country exists or participates as a relevant actor during a specified war or armed conflict.
-
B.
statusDuringWar
Indicates the role, condition, or classification an entity held specifically during a period of war.
-
C.
stateDuringWar
Indicates that a state or condition exists specifically in the context of, or for the duration of, a war or armed conflict.
-
D.
affiliationDuringWar
chosen
Indicates the relationship of an entity’s formal or de facto alignment, support, or membership with a side or organization specifically during a wartime period.
-
E.
supportedDuringWar
Indicates that one entity provided assistance, resources, or backing to another entity specifically during a time of war.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 27, 2026, 9:40 a.m.