Triple
T24151713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Beirut |
E598552
|
entity |
| Predicate | notableMilitiaPresence |
P14275
|
FINISHED |
| Object | Kataeb Regulatory Forces |
—
|
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: Kataeb Regulatory Forces | Statement: [East Beirut, notableMilitiaPresence, Kataeb Regulatory Forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableMilitiaPresence Context triple: [East Beirut, notableMilitiaPresence, Kataeb Regulatory Forces]
-
A.
hasMilitaryPresence
chosen
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
B.
civilianPresence
Indicates the presence or involvement of non-combatant individuals in a given location, situation, or event.
-
C.
militaryActivity
Indicates that an entity is engaged in, associated with, or affected by actions, operations, or preparations conducted by armed forces.
-
D.
nearMilitaryInstallation
Indicates that one entity is located in close physical proximity to a military installation or facility.
-
E.
hasFormerMilitaryInstallationNearby
Indicates that an entity is located close to a site where a military installation previously existed but is no longer active.
- 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_69e288c9e488819093dd1acd91b08b8a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e108308190ba8740590a1c5130 |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:30 p.m.