Triple
T27172624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عماد فايز مغنية |
E682959
|
entity |
| Predicate | المنطقة التي ينتمي إليها |
P86016
|
FINISHED |
| Object | جنوب لبنان |
—
|
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: جنوب لبنان | Statement: [عماد فايز مغنية, المنطقة التي ينتمي إليها, جنوب لبنان]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: المنطقة التي ينتمي إليها Context triple: [عماد فايز مغنية, المنطقة التي ينتمي إليها, جنوب لبنان]
-
A.
regionOfAssociation
chosen
Indicates a broader geographic or spatial area with which an entity is functionally, contextually, or organizationally associated.
-
B.
所在地エリア
Indicates the geographical area or region in which an entity is located or based.
-
C.
regionFrom
Indicates that something originates from, is derived from, or is associated with a particular geographic or administrative region.
-
D.
belongsToLinguisticRegion
Indicates that one linguistic entity (such as a language, dialect, or speech variety) is associated with or situated within a particular linguistic region or area.
-
E.
belongsToEthnographicRegion
Indicates that an entity is associated with or situated within a specific ethnographic region defined by shared cultural or ethnic characteristics.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62549039c8190af7159d07416c985 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:24 a.m.