Triple
T3001859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israel Border Police |
E81805
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Magav
Magav is the Hebrew name for Israel’s Border Police, a gendarmerie-style force responsible for border security, counterterrorism, and law enforcement in sensitive areas.
|
E319271
|
NE FINISHED |
How this triple was built (4 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: Magav | Statement: [Israel Border Police, alsoKnownAs, Magav]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magav Context triple: [Israel Border Police, alsoKnownAs, Magav]
-
A.
Mata
Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
-
B.
Mvezo
Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
-
C.
Mightylele
"Mightylele" is a popular dancehall/reggae track by Ghanaian artist Stonebwoy, known for its energetic rhythm and catchy, Afrobeat-infused style.
-
D.
Máfil
Máfil is a small town and commune located in southern Chile's Los Ríos Region, known for its rural character and forestry-based economy.
-
E.
Miga
Miga is one of the official mascots of the 2010 Winter Olympics in Vancouver, depicted as a playful sea bear inspired by orcas and First Nations legends.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Magav Triple: [Israel Border Police, alsoKnownAs, Magav]
Generated description
Magav is the Hebrew name for Israel’s Border Police, a gendarmerie-style force responsible for border security, counterterrorism, and law enforcement in sensitive areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magav Target entity description: Magav is the Hebrew name for Israel’s Border Police, a gendarmerie-style force responsible for border security, counterterrorism, and law enforcement in sensitive areas.
-
A.
Mata
Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
-
B.
Mvezo
Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
-
C.
Mightylele
"Mightylele" is a popular dancehall/reggae track by Ghanaian artist Stonebwoy, known for its energetic rhythm and catchy, Afrobeat-infused style.
-
D.
Máfil
Máfil is a small town and commune located in southern Chile's Los Ríos Region, known for its rural character and forestry-based economy.
-
E.
Miga
Miga is one of the official mascots of the 2010 Winter Olympics in Vancouver, depicted as a playful sea bear inspired by orcas and First Nations legends.
- F. None of above. chosen
Provenance (5 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a11b4bc81909ce06121361b4e0f |
completed | March 8, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e4f02248190890eb3944299bd15 |
completed | March 11, 2026, 8:56 a.m. |
| NEDg | Description generation | batch_69b12eb153b481909251dd72a7ca55d4 |
completed | March 11, 2026, 8:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1d65c9550819081e8734cece6ff13 |
completed | March 11, 2026, 8:53 p.m. |
Created at: March 8, 2026, 2:59 p.m.